9206 Spark Jobs - Page 2

Name List Screening and Transaction Screening Model Strats, AS Role Description Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Banks business and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank. You will work within the Global Strategic Analytics Team as part of a global model strategy and deployment of Name List Screening and Transaction Screening. To be successful in that role, you will be familiar with the most recent data science methodologies and have a delivery-centric attitude, strong analytical skills, and a detail-oriented approach to breaking down complex matters into more understandable details. The purpose of Name List Screening and Transaction Screening is to identify and investigate unusual customer names and transactions and behavior, to understand if that activity is considered suspicious from a financial crime perspective, and to report that activity to the government. You will be responsible for helping to implement and maintain the models for Name List Screening and Transaction Screening to ensure that all relevant criminal risks, typologies, products, and services are properly monitored. We are looking for a high-performing Associate in financial crime model development, tuning, and analytics to support the global strategy for screening systems across Name List Screening (NLS) and Transaction Screening (TS). This role offers the opportunity to work on key model initiatives within a cross-regional team and contribute directly to the banks risk mitigation efforts against financial crime. You will support model tuning and development efforts, support regulatory deliverables, and help collaborate with cross-functional teams including Compliance, Data Engineering, and Technology. Your key responsibilities Support the design and implementation of the model framework for name and transaction screening including coverage, data, model development and optimisation. Support key data initiatives, including but not limited to, data lineage, data quality controls, and data quality issues management. Document model logic and liaise with Compliance and Model Risk Management teams to ensure screening systems and scenarios adhere to all model governance standards Participate in research projects on innovative solutions to make detection models more pro-active Assist in model testing, calibration and performance monitoring. Ensure detailed metrics & reporting are developed to provide transparency and maintain effectiveness of name and transaction screening models. Support all examinations and reviews performed by regulators, monitors, and internal audit Your skills and experience Advanced degree (Masters or PhD) in a quantitative discipline (Mathematics, Computer Science, Data Science, Physics or Statistics) 1-3 years experience in data analytics or model development (internships included). Proficiency in designing, implementing (python, spark, cloud environments) and deploying quantitative models in a large financial institution, preferably in Front Office. Hands-on approach needed. Experience utilizing Machine Learning and Artificial Intelligence Experience with data and the ability to clearly articulate data requirements as they relate to NLS and TS, including comprehensiveness, quality, accuracy and integrity Knowledge of the banks products and services, including those related to corporate banking, investment banking, private banking, and asset management

Design, develop, and maintain scalable data processing applications using Spark and PySpark API Development 5+ years of experience in at least one of the following: Java, Spark, scala, Python API Development expertise. Write efficient, reusable, and well-documented code. Design and implement data pipelines using tools like Spark and PySpark. Strong analytical and problem-solving abilities to address technical challenges. Perform code reviews and provide constructive feedback to improve code quality. Design and implement data processing tasks that integrate with SQL databases. Proficiency in data modeling, data lake, lakehouse, and data warehousing concepts. Experience with cloud platforms like AWS

Group Strategic Analytics (GSA) is part of Group Chief Operation Office (COO) which acts as the bridge between the Banks business and infrastructure functions to help deliver the efficiency, control, and transformation goals of the Bank. You will work within the Global Strategic Analytics Team as part of a global model strategy and deployment of Name List Screening and Transaction Screening. To be successful in that role, you will be familiar with the most recent data science methodologies and have a delivery-centric attitude, strong analytical skills, and a detail-oriented approach to breaking down complex matters into more understandable details. The purpose of Name List Screening and Transaction Screening is to identify and investigate unusual customer names and transactions and behavior, to understand if that activity is considered suspicious from a financial crime perspective, and to report that activity to the government. You will be responsible for helping to implement and maintain the models for Name List Screening and Transaction Screening to ensure that all relevant criminal risks, typologies, products, and services are properly monitored. We are looking for a high-performing Associate in financial crime model development, tuning, and analytics to support the global strategy for screening systems across Name List Screening (NLS) and Transaction Screening (TS). This role offers the opportunity to work on key model initiatives within a cross-regional team and contribute directly to the banks risk mitigation efforts against financial crime. You will support model tuning and development efforts, support regulatory deliverables, and help collaborate with cross-functional teams including Compliance, Data Engineering, and Technology. Your key responsibilities Support the design and implementation of the model framework for name and transaction screening including coverage, data, model development and optimisation. Support key data initiatives, including but not limited to, data lineage, data quality controls, and data quality issues management. Document model logic and liaise with Compliance and Model Risk Management teams to ensure screening systems and scenarios adhere to all model governance standards Participate in research projects on innovative solutions to make detection models more pro-active Assist in model testing, calibration and performance monitoring. Ensure detailed metrics & reporting are developed to provide transparency and maintain effectiveness of name and transaction screening models. Support all examinations and reviews performed by regulators, monitors, and internal audit Your skills and experience Advanced degree (Masters or PhD) in a quantitative discipline (Mathematics, Computer Science, Data Science, Physics or Statistics) 13 years experience in data analytics or model development (internships included). Proficiency in designing, implementing (python, spark, cloud environments) and deploying quantitative models in a large financial institution, preferably in Front Office. Hands-on approach needed. Experience utilizing Machine Learning and Artificial Intelligence Experience with data and the ability to clearly articulate data requirements as they relate to NLS and TS, including comprehensiveness, quality, accuracy and integrity Knowledge of the banks products and services, including those related to corporate banking, investment banking, private banking, and asset management

As a Data Engineer at IBM, you'll play a vital role in the development, design of application, provide regular support/guidance to project teams on complex coding, issue resolution and execution. Your primary responsibilities include: Lead the design and construction of new solutions using the latest technologies, always looking to add business value and meet user requirements. Strive for continuous improvements by testing the build solution and working under an agile framework. Discover and implement the latest technologies trends to maximize and build creative solutions Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience with Apache Spark (PySpark): In-depth knowledge of Sparks architecture, core APIs, and PySpark for distributed data processing. Big Data Technologies: Familiarity with Hadoop, HDFS, Kafka, and other big data tools. Data Engineering Skills: Strong understanding of ETL pipelines, data modelling, and data warehousing concepts. Strong proficiency in Python: Expertise in Python programming with a focus on data processing and manipulation. Data Processing Frameworks: Knowledge of data processing libraries such as Pandas, NumPy. SQL Proficiency: Experience writing optimized SQL queries for large-scale data analysis and transformation. Cloud Platforms: Experience working with cloud platforms like AWS, Azure, or GCP, including using cloud storage systems Preferred technical and professional experience Define, drive, and implement an architecture strategy and standards for end-to-end monitoring. Partner with the rest of the technology teams including application development, enterprise architecture, testing services, network engineering, Good to have detection and prevention tools for Company products and Platform and customer-facing

Implementing and validating predictive models as well as creating and maintaining statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques. Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements. Working in an Agile, collaborative environment, partnering with other scientists, engineers, consultants, and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors. Building teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modeling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise BE / B Tech in any stream, M.Sc. (Computer Science/IT) / M.C.A, with Minimum 3-5 plus years of experience Experience in Front-End Development specializing in React.js and TypeScript , Javascript, MySql Ability to use Extract, Transform, and Load (ETL) tools and/or data integration, or federation tools to prepare and transform data as needed. Ability to use leading edge tools such as Linux, SQL, Python, Spark, Hadoop, and Java. Proficient understanding of code version tools such as GitHub, Gitlab, Bitbucket Preferred technical and professional experience You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions. Ability to communicate results to technical and non-technical audiences

Create Solution Outline and Macro Design to describe end to end product implementation in Data Platforms including, System integration, Data ingestion, Data processing, Serving layer, Design Patterns, Platform Architecture Principles for Data platform. Contribute to pre-sales, sales support through RfP responses, Solution Architecture, Planning and Estimation. Contribute to reusable components / asset / accelerator development to support capability development Participate in Customer presentations as Platform Architects / Subject Matter Experts on Big Data, Azure Cloud and related technologies Participate in customer PoCs to deliver the outcomes Participate in delivery reviews / product reviews, quality assurance and work as design authority Required education Bachelor's Degree Preferred education Non-Degree Program Required technical and professional expertise Experience in designing of data products providing descriptive, prescriptive, and predictive analytics to end users or other systems Experience in data engineering and architecting data platforms. Experience in architecting and implementing Data Platforms Azure Cloud Platform Experience on Azure cloud is mandatory (ADLS Gen 1 / Gen2, Data Factory, Databricks, Synapse Analytics, Azure SQL, Cosmos DB, Event hub, Snowflake), Azure Purview, Microsoft Fabric, Kubernetes, Terraform, Airflow Experience in Big Data stack (Hadoop ecosystem Hive, HBase, Kafka, Spark, Scala PySpark, Python etc.) with Cloudera or Hortonworks Preferred technical and professional experience Experience in architecting complex data platforms on Azure Cloud Platform and On-Prem Experience and exposure to implementation of Data Fabric and Data Mesh concepts and solutions like Microsoft Fabric or Starburst or Denodo or IBM Data Virtualisation or Talend or Tibco Data Fabric Exposure to Data Cataloging and Governance solutions like Collibra, Alation, Watson Knowledge Catalog, dataBricks unity Catalog, Apache Atlas, Snowflake Data Glossary etc

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs. Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Design, develop, and maintain Ab Initio graphs for extracting, transforming, and loading (ETL) data from diverse sources to various target systems. Implement data quality and validation processes within Ab Initio.. Data Modeling and Analysis:. Collaborate with data architects and business analysts to understand data requirements and translate them into effective ETL processes.. Analyze and model data to ensure optimal ETL design and performance.. Ab Initio Components:. . Utilize Ab Initio components such as Transform Functions, Rollup, Join, Normalize, and others to build scalable and efficient data integration solutions.. Implement best practices for reusable Ab Initio component Preferred technical and professional experience Optimize Ab Initio graphs for performance, ensuring efficient data processing and minimal resource utilization.. Conduct performance tuning and troubleshooting as needed.. Collaboration. Work closely with cross-functional teams, including data analysts, database administrators, and quality assurance, to ensure seamless integration of ETL processes.. Participate in design reviews and provide technical expertise to enhance overall solution quality Documentation

As a Big Data Engineer, you will develop, maintain, evaluate, and test big data solutions. You will be involved in data engineering activities like creating pipelines/workflows for Source to Target and implementing solutions that tackle the clients needs Your primary responsibilities include: Design, build, optimize and support new and existing data models and ETL processes based on our clients business requirements. Build, deploy and manage data infrastructure that can adequately handle the needs of a rapidly growing data driven organization. Coordinate data access and security to enable data scientists and analysts to easily access to data whenever they need too Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Design, develop, and maintain Ab Initio graphs for extracting, transforming, and loading (ETL) data from diverse sources to various target systems. Implement data quality and validation processes within Ab Initio. Data Modelling and Analysis. Collaborate with data architects and business analysts to understand data requirements and translate them into effective ETL processes. Analyse and model data to ensure optimal ETL design and performance. Ab Initio Components. . Utilize Ab Initio components such as Transform Functions, Rollup, Join, Normalize, and others to build scalable and efficient data integration solutions. Implement best practices for reusable Ab Initio components Preferred technical and professional experience Optimize Ab Initio graphs for performance, ensuring efficient data processing and minimal resource utilization. Conduct performance tuning and troubleshooting as needed. Collaboration. . Work closely with cross-functional teams, including data analysts, database administrators, and quality assurance, to ensure seamless integration of ETL processes. Participate in design reviews and provide technical expertise to enhance overall solution quality Documentation

Developer leads the cloud application development/deployment. A developer responsibility is to lead the execution of a project by working with a level resource on assigned development/deployment activities and design, build, and maintain cloud environments focusing on uptime, access, control, and network security using automation and configuration management tools Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Strong proficiency in Java, Spring Framework, Spring boot, RESTful APIs, excellent understanding of OOP, Design Patterns. Strong knowledge of ORM tools like Hibernate or JPA, Java based Micro-services framework, Hands on experience on Spring boot Microservices Strong knowledge of micro-service logging, monitoring, debugging and testing, In-depth knowledge of relational databases (e.g., MySQL) Experience in container platforms such as Docker and Kubernetes, experience in messaging platforms such as Kafka or IBM MQ, Good understanding of Test-Driven-Development Familiar with Ant, Maven or other build automation framework, good knowledge of base UNIX commands Preferred technical and professional experience Experience in Concurrent design and multi-threading Primary Skills: - Core Java, Spring Boot, Java2/EE, Microservices - Hadoop Ecosystem (HBase, Hive, MapReduce, HDFS, Pig, Sqoop etc) - Spark Good to have Python

As an Associate Software Developer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience in Big Data Technology like Hadoop, Apache Spark, Hive. Practical experience in Core Java (1.8 preferred) /Python/Scala. Having experience in AWS cloud services including S3, Redshift, EMR etc. Strong expertise in RDBMS and SQL. Good experience in Linux and shell scripting. Experience in Data Pipeline using Apache Airflow Preferred technical and professional experience You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

The ability to be a team player The ability and skill to train other people in procedural and technical topics Strong communication and collaboration skills Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Able to write complex SQL queries; Having experience in Azure Databricks Preferred technical and professional experience Excellent communication and stakeholder management skills

As a Data Engineer at IBM, you'll play a vital role in the development, design of application, provide regular support/guidance to project teams on complex coding, issue resolution and execution. Your primary responsibilities include: Lead the design and construction of new solutions using the latest technologies, always looking to add business value and meet user requirements. Strive for continuous improvements by testing the build solution and working under an agile framework. Discover and implement the latest technologies trends to maximize and build creative solutions Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Experience with Apache Spark (PySpark): In-depth knowledge of Sparks architecture, core APIs, and PySpark for distributed data processing. Big Data Technologies: Familiarity with Hadoop, HDFS, Kafka, and other big data tools. Data Engineering Skills: Strong understanding of ETL pipelines, data modeling, and data warehousing concepts. Strong proficiency in Python: Expertise in Python programming with a focus on data processing and manipulation. Data Processing Frameworks: Knowledge of data processing libraries such as Pandas, NumPy. SQL Proficiency: Experience writing optimized SQL queries for large-scale data analysis and transformation. Cloud Platforms: Experience working with cloud platforms like AWS, Azure, or GCP, including using cloud storage systems Preferred technical and professional experience Define, drive, and implement an architecture strategy and standards for end-to-end monitoring. Partner with the rest of the technology teams including application development, enterprise architecture, testing services, network engineering, Good to have detection and prevention tools for Company products and Platform and customer-facing

As an Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education High School Diploma/GED Required technical and professional expertise Good Hands on experience in DBT is required. ETL Datastage and snowflake - preferred. Ability to use programming languages like Java, Python, Scala, etc., to build pipelines to extract and transform data from a repository to a data consumer Ability to use Extract, Transform, and Load (ETL) tools and/or data integration, or federation tools to prepare and transform data as needed. Ability to use leading edge tools such as Linux, SQL, Python, Spark, Hadoop and Java Preferred technical and professional experience You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

As Data Engineer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. Youll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, youll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, youll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviours. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Expertise in designing and implementing scalable data warehouse solutions on Snowflake, including schema design, performance tuning, and query optimization. Strong experience in building data ingestion and transformation pipelines using Talend to process structured and unstructured data from various sources. Proficiency in integrating data from cloud platforms into Snowflake using Talend and native Snowflake capabilities. Hands-on experience with dimensional and relational data modelling techniques to support analytics and reporting requirements Preferred technical and professional experience Understanding of optimizing Snowflake workloads, including clustering keys, caching strategies, and query profiling. Ability to implement robust data validation, cleansing, and governance frameworks within ETL processes. Proficiency in SQL and/or Shell scripting for custom transformations and automation tasks

About the Role: Seeking a highly skilled Senior Data Engineer with 8 years of experience to join our dynamic team. Requirements: Experienced in architecting, building and maintaining end-to-end data pipelines using Python and Spark in Databricks Proficient in designing and implementing scalable data lake and data warehouse solutions on Azure including Azure Data Lake, Data Factory, Synapse and Azure SQL Hands on experience in leading the integration of complex data sources and the development of efficient ETL processes Champion best practices in data governance, data quality and data security across the organization Adept in collaborating closely with data scientists, analysts and business stakeholders to deliver high-impact data solutions. #LI-MS2 #LI-Onsite

As an Associate Software Developer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You'll contribute to data gathering, storage, and both batch and real-time processing. Collaborating closely with diverse teams, you'll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you'll tackle obstacles related to database integration and untangle complex, unstructured data sets. In this role, your responsibilities may include: Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques Designing and implementing various enterprise seach applications such as Elasticsearch and Splunk for client requirements Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviors. Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modeling results Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise Develop/Convert the database (Hadoop to GCP) of the specific objects (tables, views, procedures, functions, triggers, etc.) from one database to another database platform Implementation of a specific Data Replication mechanism (CDC, file data transfer, bulk data transfer, etc.). Expose data as API Participation in modernization roadmap journey Analyze discovery and analysis outcomes Lead discovery and analysis workshops/playbacks Identification of the applications dependencies, source, and target database incompatibilities. Analyze the non-functional requirements (security, HA, RTO/RPO, storage, compute, network, performance bench, etc.). Prepare the effort estimates, WBS, staffing plan, RACI, RAID etc. . Leads the team to adopt right tools for various migration and modernization method Preferred technical and professional experience You thrive on teamwork and have excellent verbal and written communication skills. Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions Ability to communicate results to technical and non-technical audiences

As Data Engineer, you will develop, maintain, evaluate and test big data solutions. You will be involved in the development of data solutions using Spark Framework with Python or Scala on Hadoop and AWS Cloud Data Platform Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise AWS Data Vault 2.0 development mechanism for agile data ingestion, storage and scaling Databricks for complex queries on transformation, aggregation, business logic implementation aggregation, business logic implementation AWS Redshift and Redshift spectrum, for complex queries on transformation, aggregation, business logic implementation DWH Concept on star schema, Materialize view concept. Strong SQL and data manipulation/transformation skills Preferred technical and professional experience Robust and Scalable Cloud Infrastructure End-to-End Data Engineering Pipeline Versatile Programming Capabilities

Company: Mercer Description: About the role Location Gurugram Functional Area Software Engineering Education Qualification BTech/MTech from tier 1 colleges Experience: 8+ years Key Responsibilities Own and deliver complete features across the development lifecycle, including design, architecture, implementation, testability, debugging, shipping, and servicing. Write and review clean, well-thought-out code with an emphasis on quality, performance, simplicity, durability, scalability, and maintainability Performing data analysis to identify opportunities to optimize services Leading discussions for the architecture of products/solutions, refine code plans Working on research and development in cutting edge accelerations and optimizations Mentoring junior team members in their growth and development Collaborating with Product Managers, Architects, and UX Designers on new features. Core Technology skills - Java/J2EE, Full stack development, Python, Micro services, , SQL/NO SQL Databases, Cloud (AWS), API development and other open source technologies 8+years experiencebuilding highly available distributed systems at scale Configuration Management (Terraform, Chef, Puppet or Ansible) Problem-solving skills to determine the cause of bugs and resolve complaints Strong organizational skills, including an ability to perform under pressure and manage multiple priorities with competing demands for resources. Mercer, a business of Marsh McLennan (NYSEMMC), is a global leader in helping clients realize their investment objectives, shape the future of work and enhance health and retirement outcomes for their people. Marsh McLennan is a global leader in risk, strategy and people, advising clients in 130 countries across four businessesMarsh, Guy Carpenter, Mercer and Oliver Wyman. With annual revenue of $24 billion and more than 90,000 colleagues, Marsh McLennan helps build the confidence to thrive through the power of perspective. For more information, visit mercer.com, or follow on LinkedIn and X. Marsh McLennan is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age, background, caste, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. Marsh McLennan is committed to hybrid work, which includes the flexibility of working remotely and the collaboration, connections and professional development benefits of working together in the office. All Marsh McLennan colleagues are expected to be in their local office or working onsite with clients at least three days per week. Office-based teams will identify at least one anchor day per week on which their full team will be together in person.

Analytics - Risk Product Paytm is India's leading mobile payments and financial services distribution company. Pioneer of the mobile QR payments revolution in India, Paytm builds technologies that help small businesses with payments and commerce. Paytm s mission is to serve half a billion Indians and bring them to the mainstream economy with the help of technology. About the Role: We seek an experienced Assistant General Manager - Analytics for data analysis and reporting across our lending verticals. The ideal candidate will use SQL and dashboarding tools to deliver actionable insights and manage data needs for multiple lending verticals. A drive to implement AI to automate repetitive workflows is essential. Key Responsibilities: Develop, maintain, and automate reporting and dashboards for lending vertical KPIs. Manage data and analytics requirements for multiple lending verticals. Collaborate with stakeholders to understand data needs and provide support. Analyze data trends to provide insights and recommendations. Design and implement data methodologies to improve data quality. Ensure data accuracy and integrity. Communicate findings to technical and non-technical audiences. Stay updated on data analytics trends and identify opportunities for AI implementation. Drive the use of AI to automate repetitive data workflows. Qualifications Bachelor's degree in a quantitative field. 5-7 years of data analytics experience. Strong SQL and Pyspark proficiency. Experience with data visualization tools (e.g., Tableau, Power BI, Looker). Lending/financial services experience is a plus. Excellent analytical and problem-solving skills. Strong communication and presentation skills. Ability to manage multiple projects. Ability to work independently and in a team. Demonstrated drive to use and implement AI for automation. Preferred Qualifications Experience with statistical modeling and data mining. Familiarity with cloud data warehousing (e.g., Snowflake, BigQuery, Redshift). Experience with Python or R. Experience implementing AI solutions in a business setting Why Join us Bragging rights to be behind the largest fintech lending play in India A fun, energetic and a once-in-a-lifetime environment that enables you to achieve your best possible outcome in your career With enviable 500 mn+ registered users, 21 mn+ merchants and depth of data in our ecosystem, we are in a unique position to democratize credit for deserving consumers & merchants - and we are committed to it. India s largest digital lending story is brewing here. It s your opportunity to be a part of the story!

Hello Visionary! We empower our people to stay resilient and relevant in a constantly changing world. We’re looking for people who are always searching for creative ways to grow and learn. People who want to make a real impact, now and in the future. Does that sound like youThen it seems like you’d make a great addition to our vibrant team. Siemens founded the new business unit Siemens Foundational Technologies (formerly known as Siemens IoT Services) on April 1, 2019 with its headquarter in Munich, Germany. It has been crafted to unlock the digital future of its clients by offering end-to-end support on their outstanding digitalization journey. Siemens Foundational Technologies is a strategic advisor and a trusted implementation partner in digital transformation and industrial IoT with a global network of more than 8000 employees in 10 countries and 21 offices. Highly skilled and experienced specialists offer services which range from consulting to craft & prototyping to solution & implementation and operation – everything out of one hand. We are looking for a Senior Software Engineer - Embedded You’ll make a difference by: Overview: Be a member of the international engineering team Configure and customize Debian Linux image for deployment to the train Customize applications and configure devices such as network switches and special devices according to the system architecture of the train Integrate these applications and devices with other systems in the train Cooperate with software test team Provide technical support in your area of expertise Your qualification: Experience with Linux as power user or administrator (4-6Years) Experience with configuration of managed switches Good knowledge of TCP/IP Understanding of network protocols like DHCP, RADIUS, DNS, multicast, SSL/TLS Experience with issue tracking tools such as JIRA or Redmine Fluent English Highly organized and self-motivated Hands-on, problem-solving mentality This would set you apart from other candidates: Experience in the railway industry or automotive Long term interest in the IT domain, passion for IT German language Python programming Desired Skills: 5-8 years of experience is required. Great Communication skills. Analytical and problem-solving skills Join us and be yourself! Make your mark in our exciting world at Siemens. This role is based in Pune and is an Individual contributor role. You might be required to visit other locations within India and outside. In return, you'll get the chance to work with teams impacting - and the shape of things to come. Find out more about Siemens careers at: www.siemens.com/careers & more about mobility at https://new.siemens.com/global/en/products/mobility.html

At Capgemini Invent, we believe difference drives change. As inventive transformation consultants, we blend our strategic, creative and scientific capabilities,collaborating closely with clients to deliver cutting-edge solutions. Join us to drive transformation tailored to our client's challenges of today and tomorrow. Informed and validated by science and data. Superpowered by creativity and design. All underpinned by technology created with purpose. Data engineers are responsible for building reliable and scalable data infrastructure that enables organizations to derive meaningful insights, make data-driven decisions, and unlock the value of their data assets. - Grade Specific The role support the team in building and maintaining data infrastructure and systems within an organization. Skills (competencies) Ab Initio Agile (Software Development Framework) Apache Hadoop AWS Airflow AWS Athena AWS Code Pipeline AWS EFS AWS EMR AWS Redshift AWS S3 Azure ADLS Gen2 Azure Data Factory Azure Data Lake Storage Azure Databricks Azure Event Hub Azure Stream Analytics Azure Sunapse Bitbucket Change Management Client Centricity Collaboration Continuous Integration and Continuous Delivery (CI/CD) Data Architecture Patterns Data Format Analysis Data Governance Data Modeling Data Validation Data Vault Modeling Database Schema Design Decision-Making DevOps Dimensional Modeling GCP Big Table GCP BigQuery GCP Cloud Storage GCP DataFlow GCP DataProc Git Google Big Tabel Google Data Proc Greenplum HQL IBM Data Stage IBM DB2 Industry Standard Data Modeling (FSLDM) Industry Standard Data Modeling (IBM FSDM)) Influencing Informatica IICS Inmon methodology JavaScript Jenkins Kimball Linux - Redhat Negotiation Netezza NewSQL Oracle Exadata Performance Tuning Perl Platform Update Management Project Management PySpark Python R RDD Optimization SantOs SaS Scala Spark Shell Script Snowflake SPARK SPARK Code Optimization SQL Stakeholder Management Sun Solaris Synapse Talend Teradata Time Management Ubuntu Vendor Management Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fuelled by its market leading capabilities in AI, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 global revenues of "22.5 billion.

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand their data needs and provide effective solutions, ensuring that the data infrastructure is robust and scalable to meet the demands of the organization. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge in data engineering.- Continuously evaluate and improve data processes to enhance efficiency and effectiveness. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Experience with data integration and ETL tools.- Strong understanding of data modeling and database design principles.- Familiarity with cloud platforms and services related to data storage and processing.- Knowledge of programming languages such as Python or Scala for data manipulation. Additional Information:- The candidate should have minimum 7.5 years of experience in Databricks Unified Data Analytics Platform.- This position is based in Chennai.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand their data needs and provide effective solutions, ensuring that the data infrastructure is robust and scalable to meet the demands of the organization. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge in data engineering.- Continuously evaluate and improve data processes to enhance efficiency and effectiveness. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Experience with data integration and ETL tools.- Strong understanding of data modeling and database design principles.- Familiarity with cloud platforms and services related to data storage and processing.- Knowledge of programming languages such as Python or Scala for data manipulation. Additional Information:- The candidate should have minimum 7.5 years of experience in Databricks Unified Data Analytics Platform.- This position is based in Chennai.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and deliver effective solutions that meet business needs, while also troubleshooting and optimizing existing data workflows to enhance performance and reliability. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge in data engineering.- Continuously evaluate and improve data processes to ensure efficiency and effectiveness. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Strong understanding of data pipeline architecture and design.- Experience with ETL processes and data integration techniques.- Familiarity with data quality frameworks and best practices.- Knowledge of cloud platforms and services related to data storage and processing. Additional Information:- The candidate should have minimum 5 years of experience in Databricks Unified Data Analytics Platform.- This position is based in Hyderabad.- A 15 years full time education is required. Qualification 15 years full time education

Project Role : Data Engineer Project Role Description : Design, develop and maintain data solutions for data generation, collection, and processing. Create data pipelines, ensure data quality, and implement ETL (extract, transform and load) processes to migrate and deploy data across systems. Must have skills : Databricks Unified Data Analytics Platform Good to have skills : NAMinimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As a Data Engineer, you will design, develop, and maintain data solutions that facilitate data generation, collection, and processing. Your typical day will involve creating data pipelines, ensuring data quality, and implementing ETL processes to migrate and deploy data across various systems. You will collaborate with cross-functional teams to understand data requirements and deliver effective solutions that meet business needs, while also troubleshooting and optimizing existing data workflows to enhance performance and reliability. Roles & Responsibilities:- Expected to be an SME.- Collaborate and manage the team to perform.- Responsible for team decisions.- Engage with multiple teams and contribute on key decisions.- Provide solutions to problems for their immediate team and across multiple teams.- Mentor junior team members to enhance their skills and knowledge in data engineering.- Continuously evaluate and improve data processes to ensure efficiency and effectiveness. Professional & Technical Skills: - Must To Have Skills: Proficiency in Databricks Unified Data Analytics Platform.- Strong understanding of data pipeline architecture and design.- Experience with ETL processes and data integration techniques.- Familiarity with data quality frameworks and best practices.- Knowledge of cloud platforms and services related to data storage and processing. Additional Information:- The candidate should have minimum 5 years of experience in Databricks Unified Data Analytics Platform.- This position is based in Hyderabad.- A 15 years full time education is required. Qualification 15 years full time education