11759 Microsoft Azure Jobs - Page 38

Role Objective Technical/Domain Skills (must) Software Engineer role will be collaborating with Data Scientists and AI Engineers to develop and integrate scalable backend services, tools for agents and intuitive user interfaces that support the deployment and usability of AI-driven applications. Python, RESTful APIs & Integration, Cloud Platform (Azure), SQL, CI/CD

About the role Youll be at the heart of developing and maintaining our sophisticated in-house insurance products built primarily with Java and Spring Boot. You will have the opportunity to join one of our product teams and contribute to the development of functionality which generates real business impact. About the team We are a team that believes in engineering excellence and that our leaders should also be engineers themselves. We build applications that are carefully designed, thoughtfully implemented, and surpass the expectations of our users by working together with product owners. Quality and stability are first-class deliverables in everything we do, and we lead by example by embedding high standards into our processes. Your responsibilities include Develop and review code that meets our high standards for quality and maintainability. Collaborate effectively within a cross-functional team including requirements engineers, QA specialists, and other application engineers. Shape architecture by contributing to key decisions and documentation that guide our technical direction. Integrate services and shared platforms including messaging systems, BPMN workflows, logging frameworks, and telemetry solutions. Stay current with emerging technologies and Generative AI developments to continuously improve our solutions. About you Youre a naturally curious and thoughtful professional who thrives in a high-performance engineering environment. Your passion for coding is matched by your commitment to delivering business value. You believe in continuous learning through self-improvement or by absorbing knowledge from those around you and youre excited to contribute to a team that values technical excellence. You should bring the following skills and experiences Must be proficient in software development across the entire software delivery lifecycle, with strong Java and Spring Boot expertise Must have previous public cloud experience, particularly with Microsoft Azure Experience in modern software architecture using synchronous, asynchronous integration technologies using RabbitMQ, Azure Service Bus, or Kafka, and other technologies Proficient in relational and/or document-based database technologies covering conceptual domain model design and its physical implementation Must be comfortable spending most of your time in the IDE and working with large and established codebases About Swiss Re If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience. Keywords: Reference Code: 134105

About the role Youll be at the heart of developing and maintaining our sophisticated in-house insurance products built primarily with Java and Spring Boot. You will have the opportunity to join one of our product teams and contribute to the development of functionality which generates real business impact. About the team We are a team that believes in engineering excellence and that our leaders should also be engineers themselves. We build applications that are carefully designed, thoughtfully implemented, and surpass the expectations of our users by working together with product owners. Quality and stability are first-class deliverables in everything we do, and we lead by example by embedding high standards into our processes. Your responsibilities include Develop and review code that meets our high standards for quality and maintainability. Collaborate effectively within a cross-functional team including requirements engineers, QA specialists, and other application engineers. Shape architecture by contributing to key decisions and documentation that guide our technical direction. Integrate services and shared platforms including messaging systems, BPMN workflows, logging frameworks, and telemetry solutions. Stay current with emerging technologies and Generative AI developments to continuously improve our solutions. About you Youre a naturally curious and thoughtful professional who thrives in a high-performance engineering environment. Your passion for coding is matched by your commitment to delivering business value. You believe in continuous learning through self-improvement or by absorbing knowledge from those around you and youre excited to contribute to a team that values technical excellence. You should bring the following skills and experiences Must be proficient in software development across the entire software delivery lifecycle, with strong Java and Spring Boot expertise Must have previous public cloud experience, particularly with Microsoft Azure Experience in modern software architecture using synchronous, asynchronous integration technologies using RabbitMQ, Azure Service Bus, or Kafka, and other technologies Proficient in relational and/or document-based database technologies covering conceptual domain model design and its physical implementation Must be comfortable spending most of your time in the IDE and working with large and established codebases About Swiss Re If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience. Keywords: Reference Code: 134146

We are seeking a skilled DevOps Engineer with strong expertise in Microsoft Azure infrastructure and Azure DevOps practices. The ideal candidate will have hands-on experience building and deploying pipelines, managing virtual machine scale sets (VMSS), and working with agent pools. Proficiency in shell scripting, GitHub repository management, and excellent communication skills are essential. Experience working with large teams and handling releases will be an added advantage. Key Expectations: Proven experience managing Microsoft Azure infrastructure, preferably with an Azure Administrator certification, demonstrating deep knowledge of Azure services and best practices. Hands-on expertise with Azure DevOps, including building and deploying pipeline images, managing VM Scale Sets (VMSS), and configuring Agent Pools to support scalable and automated deployments. Strong scripting skills using Shell to automate infrastructure tasks, deployments, and monitoring processes efficiently. Proficient in using GitHub as a code repository for version control, branching strategies, and collaboration across distributed teams. Excellent verbal and written communication skills to effectively coordinate with development, QA, and operations teams, document processes, and report progress clearly. Experience working with large teams to coordinate and manage software releases, ensuring smooth deployment cycles and minimizing downtime. Ability to troubleshoot, debug, and resolve infrastructure and deployment issues promptly to maintain continuous integration and continuous delivery (CI/CD) pipelines. Familiarity with infrastructure as code (IaC) tools and practices (e.g., ARM templates, Terraform) is a plus and will enhance automation capabilities. #ProductEngineering Location: IND:AP:Hyderabad / Argus Bldg 4f & 5f, Sattva, Knowledge City- Adm: Argus Building, Sattva, Knowledge City Job ID R-72436-1 Date posted 07/18/2025

Job Summary: We are seeking a highly motivated and skilled Power Platform Consultant / Developer with 4+ years of experience in building enterprise solutions using Microsoft Power Apps (Canvas & Model-driven), Power Automate, Power BI, and Dataverse. The ideal candidate will be responsible for designing, developing, deploying, and supporting solutions that streamline business processes and deliver measurable value. Experience: 4-9 Years Location: Bangalore Mode of Work: Full Time Key Responsibilities: Solution Design & Development Design, develop, and deploy scalable solutions using Power Apps (Canvas & Model-driven), Power Automate, and Dataverse. Customize and configure applications based on business requirements. Automation & Integration Create automated workflows using Power Automate. Integrate Power Platform solutions with Microsoft 365, Dynamics 365, Azure services, and third-party APIs. Data Modeling & Management Design data models and manage entities, relationships, business rules, and role-based security in Dataverse (Common Data Service). Power BI Reporting Develop interactive Power BI reports and dashboards using data from various sources to support business decision-making. Custom Development Extend Power Platform capabilities using custom connectors, PowerShell scripts, Azure Functions, JavaScript, or C# plugins when required. User Training & Documentation Prepare technical documentation and training materials. Conduct user training sessions and support knowledge transfer initiatives. Support & Maintenance Provide ongoing technical support and maintenance for existing solutions. Troubleshoot issues and implement necessary updates and enhancements. Requirements: Bachelors degree in computer science , Information Technology, or a related field. Minimum of 4 years of hands-on experience in Power Platform (Power Apps, Power Automate, Power BI). Strong understanding of Power Apps (Canvas and Model-driven) and Dataverse. Experience building automated workflows with Power Automate. Proficiency in Power BI for creating reports and visualizations. Familiarity with Microsoft Azure (Logic Apps, Functions), SharePoint, Teams, and Microsoft 365. Excellent problem-solving skills and ability to work both independently and in a collaborative team environment. Strong communication , presentation, and stakeholder management skills. Good To Have Skills : Microsoft Certifications such as PL-100, PL-200, PL-400, PL-600. Experience integrating Power Platform with Dynamics 365 CE/CRM or Business Central. Knowledge of ALM practices using Azure DevOps for Power Platform. Exposure to governance frameworks and the Center of Excellence ( CoE ) toolkit. Experience working in Agile/Scrum methodologies.

About the role Youll be at the heart of developing and maintaining our sophisticated in-house insurance products built primarily with Java and Spring Boot. You will have the opportunity to join one of our product teams and contribute to the development of functionality which generates real business impact. About the team We are a team that believes in engineering excellence and that our leaders should also be engineers themselves. We build applications that are carefully designed, thoughtfully implemented, and surpass the expectations of our users by working together with product owners. Quality and stability are first-class deliverables in everything we do, and we lead by example by embedding high standards into our processes. Your responsibilities include Develop and review code that meets our high standards for quality and maintainability. Collaborate effectively within a cross-functional team including requirements engineers, QA specialists, and other application engineers. Shape architecture by contributing to key decisions and documentation that guide our technical direction. Integrate services and shared platforms including messaging systems, BPMN workflows, logging frameworks, and telemetry solutions. Stay current with emerging technologies and Generative AI developments to continuously improve our solutions. About you Youre a naturally curious and thoughtful professional who thrives in a high-performance engineering environment. Your passion for coding is matched by your commitment to delivering business value. You believe in continuous learning through self-improvement or by absorbing knowledge from those around you and youre excited to contribute to a team that values technical excellence. You should bring the following skills and experiences Must be proficient in software development across the entire software delivery lifecycle, with strong Java and Spring Boot expertise Must have previous public cloud experience, particularly with Microsoft Azure Experience in modern software architecture using synchronous, asynchronous integration technologies using RabbitMQ, Azure Service Bus, or Kafka, and other technologies Proficient in relational and/or document-based database technologies covering conceptual domain model design and its physical implementation Must be comfortable spending most of your time in the IDE and working with large and established codebases Years of experience required 3 5 Years About Swiss Re If you are an experienced professional returning to the workforce after a career break, we encourage you to apply for open positions that match your skills and experience. Keywords: Reference Code: 134109

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

We’re building an Agentic AI Platform that lets enterprises solve real business problems using Agentic AI workflows. From utility operations to legal document review; our mission is to let AI agents think, act, and deliver; fast, secure and locally. We’re looking for an Agentic AI Engineer who’s hungry to learn and ship. If you’re ready to build with cutting-edge frameworks like Lang Chain, CrewAI, Lang Graph, Google ADK and more and can translate real enterprise problems into intelligent multi-agent workflows, this role is for you. What You’ll Do Build and deploy AI agents using open-source agentic frameworks Explore and integrate models from OpenAI, Mistral, Gemini, Llama, Claude, etc. Use tools like Retrieval-Augmented Generation (RAG), knowledge graphs, and vector stores Work with product managers and domain experts to solve real problems (not just prototypes) Continuously test and refine agent behavior across different enterprise domains (utilities, legal, marketing, supply chain) Actively contribute to evolving our proprietary DataInsightAI platform Must-Have Skills At least 1+ years of hands-on experience implementing a enterprise level Gen AI project that has gone live. Strong Python skills (Async, FastAPI, LangChain/CrewAI or similar) Experience working with LLMs (OpenAI, Llama, Claude, Gemini, etc.) Familiar with agentic AI workflows, prompt chaining, and tool use Understanding of RAG, vector databases (like FAISS, Qdrant, Weaviate) Curiosity-driven mindset, fast learner, hands-on coder Ability to simplify complex problems and build MVPs fast Nice to Have Worked on multi-agent architectures or fine-tuned LLMs Used graph databases (Neo4j) or custom knowledge stores Experience deploying on Azure/AWS/GCP Familiarity with LangGraph or Google ADK Why Join Us? Work on cutting-edge agentic AI every day Be part of a lean team with real ownership Ship fast and solve real enterprise challenges Backed by InTimeTec, with a strong AI/ML engineering culture

About the Role: Grade Level (for internal use): 11 About the Role We are looking for a highly driven Senior Platform & Full Stack Engineer who brings passion, innovation, and deep technical experience to join our high-performing DevOps and SRE team. In this role, youll help us define, build, and scale the next generation of cloud-native, cloud-agnostic CI/CD pipelines , Infrastructure as Code (IaC) reusable workflows , and AI-driven autonomous deployments . Key Responsibilities Lead the design and implementation of reusable IaC workflows and standardized CI/CD blueprints across multiple teams. Architect and maintain cloud-agnostic deployment solutions with deep expertise in AWS and Kubernetes (EKS). Implement and optimize configuration as code practices using tools like Terraform and GitHub Actions. Partner with developers and SREs to define end-to-end infrastructure workflows covering compute, network, and storage automation. Contribute as a hands-on developer to internal tools, platforms, and APIs (Java, Go, or similar). Collaborate on cutting-edge initiatives such as Agentic AI workflows and autonomous chat-based deployments using MCP and LLM orchestration. Foster a culture of continuous innovation, high energy, and performance excellence. Required Skills & Experience 10+ years of experience in DevOps, Platform Engineering, or Full Stack Development with platform ownership. Proven experience designing Infrastructure as Code using Terraform at scale. Solid programming skills J ava ,Python, Javascript and Go preferred Expertise in CI/CD pipeline design and orchestration using GitHub Actions (and optionally ArgoCD, GitLab, Jenkins, etc.). Strong knowledge of AWS services, with hands-on experience in EKS , IAM, networking (VPCs, Route53, ALBs), storage (EBS, S3), and compute. End-to-end understanding of modern cloud infrastructure , DevSecOps, observability, and release practices. Ability to translate product/platform needs into reliable, secure, scalable infrastructure solutions . Excellent problem-solving skills and a mindset for performance, scalability, and resilience. Passion for innovation, high energy, and eagerness to experiment with emerging tech like LLMs and Agentic AI Additional Skills Experience with multi-cloud environments (Azure, GCP). Knowledge of Agentic AI systems , LLMs , or AI Ops use cases. Exposure to platform-as-product or internal developer platforms. Familiarity with Kubernetes Operators, Helm charts, and service mesh (Istio, Linkerd). Why Join Us Be part of a forward-thinking DevOps and SRE team pushing the boundaries of platform automation. Work on AI-powered workflows and define how infrastructure can be deployed through intelligent assistants. Build developer-centric platforms that make a real impact on engineering productivity and product reliability. Enjoy a culture of innovation, energy, and excellence where your ideas will be heard and executed. Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ---- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ---- IFTECH202.2 - Middle Professional Tier II (EEO Job Group)

About the Role: Grade Level (for internal use): 11 Job Description Lead ReactJS Developer: Job Overview: We are seeking a highly skilled and motivated Full Stack Developer with expertise in ReactJS. You will play a pivotal role in developing and maintaining our web applications and ensuring seamless communication between the server and user-facing elements. Key Responsibilities: Design, develop, and maintain efficient, reusable, and reliable code for the frontend components. Building reusable components and front-end libraries for future use. Translating designs and wireframes into high quality code. Optimizing components for maximum performance across a vast array of web-capable devices and browsers Write unit and integration tests to ensure the quality and reliability of code. Debug and troubleshoot issues across the entire stack, from frontend UI to backend services. Work with version control systems (e.g., Git) and continuous integration/delivery tools. Stay up-to-date with the latest industry trends and technologies to make informed recommendations and improvements. Requirements: Bachelor's degree in Computer Science, Engineering, or related field, or equivalent work experience. Should have experience leading the team and working as individual contributor. Proven experience working as a ReactJS Developer (at least 9+ years of experience), with a strong portfolio showcasing ReactJS and Node.js projects. Proficiency in frontend technologies, including React, JavaScript, HTML, and CSS. Familiarity with RESTful API design and best practices. Solid understanding of version control, particularly Git. Knowledge of cloud platforms (e.g., AWS, Azure) is a plus. Strong problem-solving skills and the ability to work both independently and in a team. Excellent communication and collaboration skills. About S&P Global Dow Jones Indic e s At S&P Dow Jones Indices, we provide iconic and innovative index solutions backed by unparalleled expertise across the asset-class spectrum. By bringing transparency to the global capital markets, we empower investors everywhere to make decisions with conviction. Were the largest global resource for index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500 and the Dow Jones Industrial Average . More assets are invested in products based upon our indices than any other index provider in the world. With over USD 7.4 trillion in passively managed assets linked to our indices and over USD 11.3 trillion benchmarked to our indices, our solutions are widely considered indispensable in tracking market performance, evaluating portfolios and developing investment strategies. S&P Dow Jones Indices is a division of S&P Global (NYSE: SPGI). S&P Global is the worlds foremost provider of credit ratings, benchmarks, analytics and workflow solutions in the global capital, commodity and automotive markets. With every one of our offerings, we help many of the worlds leading organizations navigate the economic landscape so they can plan for tomorrow, today. For more information, visit . Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & Wellness: Health care coverage designed for the mind and body. Family Friendly Perks: Its not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. 20 - Professional (EEO-2 Job Categories-United States of America), IFTECH202.2 - Middle Professional Tier II (EEO Job Group), SWP Priority Ratings - (Strategic Workforce Planning)

About the Role: Grade Level (for internal use): 10 The Team: Do you love to collaborate & provide solutions? This team comes together across eight different locations every single day to craft enterprise grade applications that serve a large customer base with growing demand and usage. You will use a wide range of technologies and cultivate a collaborative environment with other internal teams. The Impact: We focus primarily developing, enhancing and delivering required pieces of information & functionality to internal & external clients in all client-facing applications. You will have a highly visible role where even small changes have very wide impact. Whats in it for you? - Opportunities for innovation and learning new state of the art technologies - To work in pure agile & scrum methodology Responsibilities: Design, and implement software-related projects. Perform analyses and articulate solutions. Design underlying engineering for use in multiple product offerings supporting a large volume of end-users. Develop project plans with task breakdowns and estimates. Manage and improve existing solutions. Solve a variety of complex problems and figure out possible solutions, weighing the costs and benefits. What were Looking For: Basic Qualifications: Bachelor's degree in Computer Science or Equivalent 7+ years related experience Passionate, smart, and articulate developer Strong C#, .Net and SQL skills Experience implementing: Web Services (with WCF, RESTful JSON, SOAP, TCP), Windows Services, and Unit Tests Dependency Injection Able to demonstrate strong OOP skills Able to work well individually and with a team Strong problem-solving skills Good work ethic, self-starter, and results-oriented Agile/Scrum experience a plus. Exposure to Data Engineering and Big Data technologies like Hadoop, Big data processing engines/Scala, Nifi and ETL is a plus. Experience of Container platforms is a plus Experience working in cloud computing environment like AWS, Azure , GCP etc. Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & Wellness: Health care coverage designed for the mind and body. Family Friendly Perks: Its not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. Recruitment Fraud Alert: If you receive an email from a spglobalind.com domain or any other regionally based domains, it is a scam and should be reported to . S&P Global never requires any candidate to pay money for job applications, interviews, offer letters, pre-employment training or for equipment/delivery of equipment. Stay informed and protect yourself from recruitment fraud by reviewing our guidelines, fraudulent domains, and how to report suspicious activity . ----------------------------------------------------------- S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. ----------------------------------------------------------- , SWP Priority Ratings - (Strategic Workforce Planning)

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

Strong experience with CI/CD tools: Azure DevOps,Jenkins,TeamCity. Proficient in scripting: PowerShell, Groovy, YAML,PowerCLI, InstallShield. Hands-on exp. with Terraform. Solid understanding of Azure or AWS cloud services. Required Candidate profile Desired Skills:Azure, powershell, yaml, terraform. Experience with Jira, Bitbucket, and Confluence. Familiarity with DevOps best practices and agile methodologies.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

IA-Consultant-Data Engineer SSIS ADF : Elevate Your Impact Through Innovation and Learning Evalueserve is a global leader in deliveringinnovative and sustainable solutions to a diverse range of clients, includingover 30% of Fortune 500 companies. With a presence in more than 45 countriesacross five continents, we excel in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevateour clients' business impact and strategic decision-making. Our team of over4, 500 talented professionals operates in countries such as India, China, Chile, Romania, the US, and Canada. Our global network also extends to emergingmarkets like Colombia, the Middle East, and the rest of Asia-Pacific.Recognized by Great Place to Work in India, Chile, Romania, the US, andthe UK in 2022, we offer a dynamic, growth-oriented, and meritocracy-basedculture that prioritizes continuous learning and skill development, work-lifebalance, and equal opportunity for all. About Insights & Advisory We are a global professional services provider offering research, analytics, and business process support services enabled by our innovative 'mind + machine' approach. We are working with over 300+ Fortune 1000 companies. Our TMT team, cater to 4 of the top 5 global Telecom & Networking Infrastructure companies as well as biggest public cloud providers. About this role We are looking for a skilled and motivated Data Engineer/Analyst with 45 years of experience in data engineering, particularly in migrating on-premises systems to cloud-based environments. This role requires strong expertise in SQL Server, SSIS, Azure Data Factory (ADF), Power BI and Microsoft Fabric. The ideal candidate will have hands-on experience designing, developing, and deploying scalable data solutions in Azure, ensuring seamless data integration and high performance. What you will be doing at Evalueserve Lead and execute the migration of on-premises SQL Server databases to Azure SQL. Migrate and modernize legacy SSIS packages from the file system to Azure Data Factory pipelines. Manage end-to-end Microsoft Fabric migration projects, including planning, execution, and post-migration validation. Design and develop stored procedures, SSIS packages, and ADF pipelines to support business data needs. Collaborate with cross-functional teams to understand requirements and deliver scalable, production-ready data solutions. Ensure data quality, workflow optimization, and performance tuning across all stages of data processing What we are looking for 45 years of hands-on experience in data engineering. Proven expertise in SQL Server (on-premises and Azure SQL). Strong experience in SSIS package development and migration. Proficiency in Azure Data Factory (ADF) and cloud-based data integration. Experience with Microsoft Fabric migration and implementation. Proficient with Power BI and Symantec Data Models, measure and views. Solid knowledge of T-SQL, stored procedures, and query optimization. Preferred Qualifications Relevant Microsoft certifications (e.g., Azure Data Engineer Associate) are a plus. Experience with DevOps practices for data pipelines. Strong communication and collaboration skills. Follow us on https://www.linkedin.com/compan y/evalueserve/ Click here to learn more about what our Leaders talking on achievements AI-poweredsupply chain optimization solution built on Google Cloud. HowEvalueserve isnow Leveraging NVIDIA NIM to enhance our AI and digital transformationsolutions and to accelerate AI Capabilities . Know more about how Evalueservehas climbed 16 places on the 50 Best Firms for Data Scientists in 2024! Want to learn more about our culture and what its like to work with us? Write to us at: careers@evalueserve.com Disclaimer: Thefollowing job description serves as an informative reference for the tasks youmay be required to perform. However, it does not constitute an integralcomponent of your employment agreement and is subject to periodic modificationsto align with evolving circumstances. Please Note :We appreciate the accuracy and authenticity of the information you provide, asit plays a key role in your candidacy. As part of the Background Verification Process, we verify your employment, education, and personal details. Please ensure allinformation is factual and submitted on time. For any assistance, your TA SPOCis available to support you .

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.

The candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The candidate must be able to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, the candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Associate Process Manager Roles and responsibilities: Leadership and Mentorship Team LeadershipLead and mentor a team of data scientists and analysts, guiding them in best practices, advanced methodologies, and career development. Project ManagementOversee multiple analytics projects, ensuring they are completed on time, within scope, and deliver impactful results. Innovation and Continuous LearningStay at the forefront of industry trends, new technologies, and methodologies, fostering a culture of innovation within the team. Collaboration with Cross-Functional Teams Stakeholder EngagementWork closely with key account managers, data analysts, and other stakeholders to understand their needs and translate them into data-driven solutions. Communication of InsightsPresent complex analytical findings clearly and actionably to non-technical stakeholders, helping guide strategic business decisions. Advanced Data Analysis and Modeling Develop Predictive ModelsCreate and validate complex predictive models for risk assessment, portfolio optimization, fraud detection, and market forecasting. Quantitative ResearchConduct in-depth quantitative research to identify trends, patterns, and relationships within large financial datasets. Statistical Analysis:Apply advanced statistical techniques to assess investment performance, asset pricing, and financial risk. Business Impact and ROI Performance MetricsDefine and track key performance indicators (KPIs) to measure the effectiveness of analytics solutions and their impact on the firm's financial performance. Cost-Benefit AnalysisPerform cost-benefit analyses to prioritize analytics initiatives that offer the highest return on investment (ROI). Algorithmic Trading and Automation Algorithm DevelopmentDevelop and refine trading algorithms that automate decision-making processes, leveraging machine learning and AI techniques. Back testing and SimulationConduct rigorous back testing and simulations of trading strategies to evaluate their performance under different market conditions. Advanced Statistical TechniquesExpertise in statistical methods such as regression analysis, time-series forecasting, hypothesis testing, and statistics. Machine Learning and AIProficiency in machine learning algorithms and experience with AI techniques, particularly in the context of predictive modeling, anomaly detection, and natural language processing (NLP). Programming LanguagesStrong coding skills in languages like Python, commonly used for data analysis, modeling, and automation. Data Management:Experience with big data technologies, and relational databases to handle and manipulate large datasets. Data VisualizationProficiency in creating insightful visualizations that effectively communicate complex data findings to stakeholders. Cloud ComputingFamiliarity with cloud platforms like AWS, Azure, or Google Cloud for deploying scalable data solutions. Quantitative AnalysisDeep understanding of quantitative finance, including concepts like pricing models, portfolio theory, and risk metrics. Algorithmic TradingExperience in developing and back testing trading algorithms using quantitative models and data-driven strategies. Technical and Functional Skills: Bachelor's degree in a related field, such as computer science, data science, or statistics. Proven experience of 5 to 7 years in programming languages, machine learning, data visualization and statistical analysis.