1885 Data Engineering Jobs - Page 34

What you will do Role Description: We are seeking a Senior Data Engineer with expertise in Graph Data technologies to join our data engineering team and contribute to the development of scalable, high-performance data pipelines and advanced data models that power next-generation applications and analytics. This role combines core data engineering skills with specialized knowledge in graph data structures, graph databases, and relationship-centric data modeling, enabling the organization to leverage connected data for deep insights, pattern detection, and advanced analytics use cases. The ideal candidate will have a strong background in data architecture, big data processing, and Graph technologies and will work closely with data scientists, analysts, architects, and business stakeholders to design and deliver graph-based data engineering solutions. Roles & Responsibilities: Design, build, and maintain robust data pipelines using Databricks (Spark, Delta Lake, PySpark) for complex graph data processing workflows. Own the implementation of graph-based data models, capturing complex relationships and hierarchies across domains. Build and optimize Graph Databases such as Stardog, Neo4j, Marklogic or similar to support query performance, scalability, and reliability. Implement graph query logic using SPARQL, Cypher, Gremlin, or GSQL, depending on platform requirements. Collaborate with data architects to integrate graph data with existing data lakes, warehouses, and lakehouse architectures. Work closely with data scientists and analysts to enable graph analytics, link analysis, recommendation systems, and fraud detection use cases. Develop metadata-driven pipelines and lineage tracking for graph and relational data processing. Ensure data quality, governance, and security standards are met across all graph data initiatives. Mentor junior engineers and contribute to data engineering best practices, especially around graph-centric patterns and technologies. Stay up to date with the latest developments in graph technology, graph ML, and network analytics. What we expect of you Must-Have Skills: Hands-on experience in Databricks, including PySpark, Delta Lake, and notebook-based development. Hands-on experience with graph database platforms such as Stardog, Neo4j, Marklogic etc. Strong understanding of graph theory, graph modeling, and traversal algorithms Proficiency in workflow orchestration, performance tuning on big data processing Strong understanding of AWS services Ability to quickly learn, adapt and apply new technologies with strong problem-solving and analytical skills Excellent collaboration and communication skills, with experience working with Scaled Agile Framework (SAFe), Agile delivery practices, and DevOps practices. Good-to-Have Skills: Good to have deep expertise in Biotech & Pharma industries Experience in writing APIs to make the data available to the consumers Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Masters degree and 3 to 4 + years of Computer Science, IT or related field experience Bachelors degree and 5 to 8 + years of Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills.

Role Description: We are looking for an Associate Data Engineer with deep expertise in writing data pipelines to build scalable, high-performance data solutions. The ideal candidate will be responsible for developing, optimizing and maintaining complex data pipelines, integration frameworks, and metadata-driven architectures that enable seamless access and analytics. This role prefers deep understanding of the big data processing, distributed computing, data modeling, and governance frameworks to support self-service analytics, AI-driven insights, and enterprise-wide data management. Roles & Responsibilities: Data Engineer who owns development of complex ETL/ELT data pipelines to process large-scale datasets Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions Ensuring data integrity, accuracy, and consistency through rigorous quality checks and monitoring Exploring and implementing new tools and technologies to enhance ETL platform and performance of the pipelines Proactively identify and implement opportunities to automate tasks and develop reusable frameworks Eager to understand the biotech/pharma domains & build highly efficient data pipelines to migrate and deploy complex data across systems Work in an Agile and Scaled Agile (SAFe) environment, collaborating with cross-functional teams, product owners, and Scrum Masters to deliver incremental value Use JIRA, Confluence, and Agile DevOps tools to manage sprints, backlogs, and user stories. Support continuous improvement, test automation, and DevOps practices in the data engineering lifecycle Collaborate and communicate effectively with the product teams, with cross-functional teams to understand business requirements and translate them into technical solutions Must-Have Skills: Experience in Data Engineering with a focus on Databricks, AWS, Python, SQL, and Scaled Agile methodologies Proficiency & Strong understanding of data processing and transformation of big data frameworks (Databricks, Apache Spark, Delta Lake, and distributed computing concepts) Strong understanding of AWS services and can demonstrate the same Ability to quickly learn, adapt and apply new technologies Strong problem-solving and analytical skills Excellent communication and teamwork skills Experience with Scaled Agile Framework (SAFe), Agile delivery, and DevOps practices Good-to-Have Skills: Data Engineering experience in Biotechnology or pharma industry Exposure to APIs, full stack development Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Education and Professional Certifications Bachelors degree and 2 to 5 + years of Computer Science, IT or related field experience OR Masters degree and 1 to 4 + years of Computer Science, IT or related field experience AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills.

ABOUT THE ROLE Role Description: We are seeking a Data Solutions Architect with deep expertise in Biotech/Pharma to design, implement, and optimize scalable and high-performance data solutions that support enterprise analytics, AI-driven insights, and digital transformation initiatives. This role will focus on data strategy, architecture, governance, security, and operational efficiency, ensuring seamless data integration across modern cloud platforms. The ideal candidate will work closely with engineering teams, business stakeholders, and leadership to establish a future-ready data ecosystem, balancing performance, cost-efficiency, security, and usability. This position requires expertise in modern cloud-based data architectures, data engineering best practices, and Scaled Agile methodologies. Roles & Responsibilities: Design and implement scalable, modular, and future-proof data architectures that initiatives in enterprise. Develop enterprise-wide data frameworks that enable governed, secure, and accessible data across various business domains. Define data modeling strategies to support structured and unstructured data, ensuring efficiency, consistency, and usability across analytical platforms. Lead the development of high-performance data pipelines for batch and real-time data processing, integrating APIs, streaming sources, transactional systems, and external data platforms. Optimize query performance, indexing, caching, and storage strategies to enhance scalability, cost efficiency, and analytical capabilities. Establish data interoperability frameworks that enable seamless integration across multiple data sources and platforms. Drive data governance strategies, ensuring security, compliance, access controls, and lineage tracking are embedded into enterprise data solutions. Implement DataOps best practices, including CI/CD for data pipelines, automated monitoring, and proactive issue resolution, to improve operational efficiency. Lead Scaled Agile (SAFe) practices, facilitating Program Increment (PI) Planning, Sprint Planning, and Agile ceremonies, ensuring iterative delivery of enterprise data capabilities. Collaborate with business stakeholders, product teams, and technology leaders to align data architecture strategies with organizational goals. Act as a trusted advisor on emerging data technologies and trends, ensuring that the enterprise adopts cutting-edge data solutions that provide competitive advantage and long-term scalability. Must-Have Skills: Experience in data architecture, enterprise data management, and cloud-based analytics solutions. Well versed in domain of Biotech/Pharma industry and has been instrumental in solving complex problems for them using data strategy. Expertise in Databricks, cloud-native data platforms, and distributed computing frameworks. Strong proficiency in modern data modeling techniques, including dimensional modeling, NoSQL, and data virtualization. Experience designing high-performance ETL/ELT pipelines and real-time data processing solutions. Deep understanding of data governance, security, metadata management, and access control frameworks. Hands-on experience with CI/CD for data solutions, DataOps automation, and infrastructure as code (IaC). Proven ability to collaborate with cross-functional teams, including business executives, data engineers, and analytics teams, to drive successful data initiatives. Strong problem-solving, strategic thinking, and technical leadership skills. Experienced with SQL/NOSQL database, vector database for large language models Experienced with data modeling and performance tuning for both OLAP and OLTP databases Experienced with Apache Spark, Apache Airflow Experienced with software engineering best-practices, including but not limited to version control (Git, Subversion, etc.), CI/CD (Jenkins, Maven etc.), automated unit testing, and Dev Ops Good-to-Have Skills: Experience with Data Mesh architectures and federated data governance models. Certification in cloud data platforms or enterprise architecture frameworks. Knowledge of AI/ML pipeline integration within enterprise data architectures. Familiarity with BI & analytics platforms for enabling self-service analytics and enterprise reporting. Education and Professional Certifications 9 to 12 years of experience in Computer Science, IT or related field AWS Certified Data Engineer preferred Databricks Certificate preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills.

Overview Deputy Director - Data Engineering PepsiCo operates in an environment undergoing immense and rapid change. Big-data and digital technologies are driving business transformation that is unlocking new capabilities and business innovations in areas like eCommerce, mobile experiences and IoT. The key to winning in these areas is being able to leverage enterprise data foundations built on PepsiCos global business scale to enable business insights, advanced analytics, and new product development. PepsiCos Data Management and Operations team is tasked with the responsibility of developing quality data collection processes, maintaining the integrity of our data foundations, and enabling business leaders and data scientists across the company to have rapid access to the data they need for decision-making and innovation. Increase awareness about available data and democratize access to it across the company. As a data engineering lead, you will be the key technical expert overseeing PepsiCo's data product build & operations and drive a strong vision for how data engineering can proactively create a positive impact on the business. You'll be empowered to create & lead a strong team of data engineers who build data pipelines into various source systems, rest data on the PepsiCo Data Lake, and enable exploration and access for analytics, visualization, machine learning, and product development efforts across the company. As a member of the data engineering team, you will help lead the development of very large and complex data applications into public cloud environments directly impacting the design, architecture, and implementation of PepsiCo's flagship data products around topics like revenue management, supply chain, manufacturing, and logistics. You will work closely with process owners, product owners and business users. You'll be working in a hybrid environment with in-house, on-premises data sources as well as cloud and remote systems. Responsibilities Data engineering lead role for D&Ai data modernization (MDIP) Ideally Candidate must be flexible to work an alternative schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon coverage requirements of the job. The candidate can work with immediate supervisor to change the work schedule on rotational basis depending on the product and project requirements. Responsibilities Manage a team of data engineers and data analysts by delegating project responsibilities and managing their flow of work as well as empowering them to realize their full potential. Design, structure and store data into unified data models and link them together to make the data reusable for downstream products. Manage and scale data pipelines from internal and external data sources to support new product launches and drive data quality across data products. Create reusable accelerators and solutions to migrate data from legacy data warehouse platforms such as Teradata to Azure Databricks and Azure SQL. Enable and accelerate standards-based development prioritizing reuse of code, adopt test-driven development, unit testing and test automation with end-to-end observability of data Build and own the automation and monitoring frameworks that captures metrics and operational KPIs for data pipeline quality, performance and cost. Collaborate with internal clients (product teams, sector leads, data science teams) and external partners (SI partners/data providers) to drive solutioning and clarify solution requirements. Evolve the architectural capabilities and maturity of the data platform by engaging with enterprise architects to build and support the right domain architecture for each application following well-architected design standards. Define and manage SLAs for data products and processes running in production. Create documentation for learnings and knowledge transfer to internal associates. Qualifications 12+ years of engineering and data management experience Qualifications 12+ years of overall technology experience that includes at least 5+ years of hands-on software development, data engineering, and systems architecture. 8+ years of experience with Data Lakehouse, Data Warehousing, and Data Analytics tools. 6+ years of experience in SQL optimization and performance tuning on MS SQL Server, Azure SQL or any other popular RDBMS 6+ years of experience in Python/Pyspark/Scala programming on big data platforms like Databricks 4+ years in cloud data engineering experience in Azure or AWS. Fluent with Azure cloud services. Azure Data Engineering certification is a plus. Experience with integration of multi cloud services with on-premises technologies. Experience with data modelling, data warehousing, and building high-volume ETL/ELT pipelines. Experience with data profiling and data quality tools like Great Expectations. Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets. Experience with at least one business intelligence tool such as Power BI or Tableau Experience with running and scaling applications on the cloud infrastructure and containerized services like Kubernetes. Experience with version control systems like ADO, Github and CI/CD tools for DevOps automation and deployments. Experience with Azure Data Factory, Azure Databricks and Azure Machine learning tools. Experience with Statistical/ML techniques is a plus. Experience with building solutions in the retail or in the supply chain space is a plus. Understanding of metadata management, data lineage, and data glossaries is a plus. BA/BS in Computer Science, Math, Physics, or other technical fields. Candidate must be flexible to work an alternative work schedule either on tradition work week from Monday to Friday; or Tuesday to Saturday or Sunday to Thursday depending upon product and project coverage requirements of the job. Candidates are expected to be in the office at the assigned location at least 3 days a week and the days at work needs to be coordinated with immediate supervisor Skills, Abilities, Knowledge: Excellent communication skills, both verbal and written, along with the ability to influence and demonstrate confidence in communications with senior level management. Proven track record of leading, mentoring data teams. Strong change manager. Comfortable with change, especially that which arises through company growth. Ability to understand and translate business requirements into data and technical requirements. High degree of organization and ability to manage multiple, competing projects and priorities simultaneously. Positive and flexible attitude to enable adjusting to different needs in an ever-changing environment. Strong leadership, organizational and interpersonal skills; comfortable managing trade-offs. Foster a team culture of accountability, communication, and self-management. Proactively drives impact and engagement while bringing others along. Consistently attain/exceed individual and team goals. Ability to lead others without direct authority in a matrixed environment. Comfortable working in a hybrid environment with teams consisting of contractors as well as FTEs spread across multiple PepsiCo locations. Domain Knowledge in CPG industry with Supply chain/GTM background is preferred.

Role & responsibilities Essential Skills: Experience: 6 to 10 yrs - Technical Expertise: Proficiency in AWS services such as Amazon S3, Redshift, EMR, Glue, Lambda, and Kinesis. Strong skills in SQL and experience with scripting languages like Python or Java. - Data Engineering Experience: Hands on experience in building and maintaining data pipelines, data modeling, and working with big data technologies. - Problem-Solving Skills: Ability to analyze complex data issues and develop effective solutions to optimize data processing and storage. - Communication and Collaboration: Strong interpersonal skills to work effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders. Educational Qualifications A bachelor's degree in computer science, information technology, or a related field is typically required. Relevant AWS certifications, such as AWS Certified Data Analytics Specialty, are advantageous

This position in the Engineering team under the Digital Experience organization. We drive the first mile of the customer experience through personalization of offers and content. We are currently on the lookout for a smart, highly driven engineer. You will be part of a team that is focused on building & managing solutions, pipelines using marketing technology stacks. You will also be expected to Identify and implement improvements including for optimizing data delivery and automate processes/pipelines. The incumbent is also expected to partner with various stakeholders, bring scientific rigor to design and develop high quality solutions. Candidate must have excellent verbal and written communication skills and be comfortable working in an entrepreneurial, startup environment within a larger company. Click here to view how Epsilon transforms marketing with 1 View, 1 Vision and 1 Voice. Brief Description of Role: Experience with both structured and unstructured data Experience working on AdTech or MarTech technologies. Experience in relational and non-relational databases and SQL (NoSQL is a plus). Understanding of Data Modeling, Data Catalog concepts and tools Ability to deal with data imperfections such as missing values, outliers, inconsistent formatting, etc. Collaborate with other members of the team to ensure high quality deliverables Learning and implementing the latest design patterns in data engineering Data Management Experience with both structured and unstructured data Experience building Data and CI/CD pipelines Experience working on AdTech or MarTech technologies is added advantage Experience in relational and non-relational databases and SQL (NoSQL is a plus). Hands on experience building ETL workflows/pipelines on large volumes of data Good understanding of Data Modeling, Data Warehouse, Data Catalog concepts and tools Able to identify, join, explore, and examine data from multiple disparate sources and formats Ability to reduce large quantities of unstructured or formless data and get it into a form in which it can be analyzed Ability to deal with data imperfections such as missing values, outliers, inconsistent formatting, etc. Development Ability to write code in programming languages such as Python and shell script on Linux Familiarity with development methodology such as Agile/Scrum Love to learn new technologies, keep abreast of the latest technologies within the cloud architecture, and drive your organization to adapt to emerging best practices Good knowledge of working in UNIX/LINUX systems Qualifications Bachelors degree in computer science with 5+ years of similar experience Tech Stack: Python, SQL, Scripting language (preferably JavaScript) Experience or knowledge on Adobe Experience Platform (RT-CDP/AEP) Experience working in Cloud Platforms (GCP or AWS) Familiarity with automated unit/integration test frameworks Good written and spoken communication skills, team player. Strong analytic thought process and ability to interpret findings

We are looking for a Data Engineer to join our team and help us to improve the platform that supports one of the best experimentation tools in the world. You will work side by side with other data engineers and site reliability engineers to improve the reliability, scalability, maintenance and operations of all the data products that are part of the experimentation tool at Booking.com. Your day to day work includes but is not limited to: maintenance and operations of data pipelines and products that handles data at big scale; the development of capabilities for monitoring, alerting, testing and troubleshooting of the data ecosystem of the experiment platform; and the delivery of data products that produce metrics for experimentation at scale. You will collaborate with colleagues in Amsterdam to achieve results the right way. This will include engineering managers, product managers, engineers and data scientists. Key Responsibilities and Duties Take ownership of multiple data pipelines and products and provide innovative solutions to reduce the operational workload required to maintain them Rapidly developing next-generation scalable, flexible, and high-performance data pipelines. Contribute to the development of data platform capabilities such as testing, monitoring, debugging and alerting to improve the development environment of data products Solve issues with data and data pipelines, prioritizing based on customer impact. End-to-end ownership of data quality in complex datasets and data pipelines. Experiment with new tools and technologies, driving innovative engineering solutions to meet business requirements regarding performance, scaling, and data quality. Provide self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise. Serve as the main point of contact for technical and business stakeholders regarding data engineering issues, such as pipeline failures and data quality concerns Role requirements Minimum 5 years of hands-on experience in data engineering as a Data Engineer or as a Software Engineer developing data pipelines and products. Bachelors degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field or 5 years of progressively responsible experience in the specialty as equivalent Solid experience in at least one programming language. We use Java and Python Experience building production data pipelines in the cloud, setting up data-lakes and server-less solutions Hands-on experience with schema design and data modeling Experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc) Knowledge of Flink, CDC, Kafka, Airflow, Snowflake, DBT or equivalent tools Practical experience building data platform capabilities like testing, alerting, monitoring, debugging, security Experience working with big data. Experience working with teams located in different timezones is a plus Experience with experimentation, statistics and A/B testing is a plus

Role Description: We are seeking a seasoned Solution Architect to drive the architecture, development and implementation of data solutions to Amgen functional groups. The ideal candidate able to work in large scale Data Analytic initiatives, engage and work along with Business, Program Management, Data Engineering and Analytic Engineering teams. Be champions of enterprise data analytic strategy, data architecture blueprints and architectural guidelines. As a Solution Architect, you will play a crucial role in designing, building, and optimizing data solutions to Amgen functional groups such as R&D, Operations and GCO. Roles & Responsibilities: Implement and manage large scale data analytic solutions to Amgen functional groups that align with the Amgen Data strategy Collaborate with Business, Program Management, Data Engineering and Analytic Engineering teams to deliver data solutions Responsible for design, develop, optimize, delivery and support of Data solutions on AWS and Databricks architecture Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions. Provide expert guidance and mentorship to the team members, fostering a culture of innovation and best practices. Be passionate and hands-on to quickly experiment with new data related technologies Define guidelines, standards, strategies, security policies and change management policies to support the Enterprise Data platform. Collaborate and align with EARB, Cloud Infrastructure, Security and other technology leaders on Enterprise Data Architecture changes Work with different project and application groups to drive growth of the Enterprise Data Platform using effective written/verbal communication skills, and lead demos at different roadmap sessions Overall management of the Enterprise Data Platform on AWS environment to ensure that the service delivery is cost effective and business SLAs around uptime, performance and capacity are met Ensure scalability, reliability, and performance of data platforms by implementing best practices for architecture, cloud resource optimization, and system tuning. Collaboration with RunOps engineers to continuously increase our ability to push changes into production with as little manual overhead and as much speed as possible. Maintain knowledge of market trends and developments in data integration, data management and analytics software/tools Work as part of team in a SAFe Agile/Scrum model Basic Qualifications and Experience: Masters degree with 6 - 8 years of experience in Computer Science, IT or related field OR Bachelors degree with 9 - 12 years of experience in Computer Science, IT or related field OR Functional Skills: Must-Have Skills: 7+ years of hands-on experience in Data integrations, Data Management and BI technology stack. Strong experience with one or more Data Management tools such as AWS data lake, Snowflake or Azure Data Fabric Expert-level proficiency with Databricks and experience in optimizing data pipelines and workflows in Databricks environments. Strong experience with Python, PySpark, and SQL for building scalable data workflows and pipelines. Experience with Apache Spark, Delta Lake, and other relevant technologies for large-scale data processing. Familiarity with BI tools including Tableau and PowerBI Demonstrated ability to enhance cost-efficiency, scalability, and performance for data solutions Strong analytical and problem-solving skills to address complex data solutions Good-to-Have Skills: Preferred to have experience in life science or tech or consultative solution architecture roles Experience working with agile development methodologies such as Scaled Agile. Professional Certifications AWS Certified Data Engineer preferred Databricks Certificate preferred Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills.

We are looking for a Snowflake Developer with deep expertise in Snowflake and DBT or SQL to help us build and scale our modern data platform. Key Responsibilities: Design and build scalable ELT pipelines in Snowflake using DBT/SQL . Develop efficient, well-tested DBT models (staging, intermediate, and marts layers). Implement data quality, testing, and monitoring frameworks to ensure data reliability and accuracy. Optimize Snowflake queries, storage, and compute resources for performance and cost-efficiency. Collaborate with cross-functional teams to gather data requirements and deliver data solutions. Required Qualifications: 5+ years of experience as a Data Engineer, with at least 4 years working with Snowflake . Proficient with DBT (Data Build Tool) including Jinja templating, macros, and model dependency management. Strong understanding of ELT patterns and modern data stack principles. Advanced SQL skills and experience with performance tuning in Snowflake. Interested candidates share your CV at himani.girnar@alikethoughts.com with below details Candidate's name- Email and Alternate Email ID- Contact and Alternate Contact no- Total exp- Relevant experience- Current Org- Notice period- CCTC- ECTC- Current Location- Preferred Location- Pancard No-

Job Description for Consultant - Data Engineer About Us: Chryselys is a Pharma Analytics & Business consulting company that delivers data-driven insights leveraging AI-powered, cloud-native platforms to achieve high-impact transformations. We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights. Who we are: People - Our team of industry veterans, advisors and senior strategists have diverse backgrounds and have worked at top tier companies. Quality - Our goal is to deliver the value of a big five consulting company without the big five cost. Technology - Our solutions are Business centric built on cloud native technologies. Key Responsibilities and Core Competencies: • You will be responsible for managing and delivering multiple Pharma projects. • Leading a team of atleast 8 members, resolving their technical and business related problems and other queries. • Responsible for client interaction; requirements gathering, creating required documents, development, quality assurance of the deliverables. • Good collaboration with onshore and Senior folks. • Should have fair understanding of Data Capabilities (Data Management, Data Quality, Master and Reference Data). • Exposure to Project management methodologies including Agile and Waterfall. • Experience working in RFPs would be a plus. Required Technical Skills: • Proficient in Python, Pyspark, SQL • Extensive hands-on experience in big data processing and cloud technologies like AWS and Azure services, Databricks etc . • Strong experience working with cloud data warehouses like Snowflake, Redshift, Azure etc. • Good experience in ETL, Data Modelling, building ETL Pipelines. • Conceptual knowledge of Relational database technologies, Data Lake, Lake Houses etc. • Sound knowledge in Data operations, quality and data governance. Preferred Qualifications: • Bachelors or master’s Engineering/ MCA or equivalent degree. • 6-13 years of experience as Data Engineer , with atleast 2 years in managing medium to large scale programs. • Minimum 5 years of Pharma and Life Science domain exposure in IQVIA, Veeva, Symphony, IMS etc. • High motivation, good work ethic, maturity, self-organized and personal initiative. • Ability to work collaboratively and providing the support to the team. • Excellent written and verbal communication skills. • Strong analytical and problem-solving skills. Location • Preferably Hyderabad, India

About Tredence: Tredence is a global data science solutions provider founded in 2013 by Shub Bhowmick, Sumit Mehra, and Shashank Dubey focused on solving the last-mile problem in AI. Headquartered in San Jose, California, the company embraces a vertical-first approach and an outcome-driven mindset to help clients win and accelerate value realization from their analytics investments. The aim is to bridge the gap between insight delivery and value realization by providing customers with a differentiated approach to data and analytics through tailor-made solutions. Tredence is 1,800-plus employees strong with offices in San Jose, Foster City, Chicago, London, Toranto, and Bangalore, with the largest companies in retail, CPG, hi-tech, telecom, healthcare, travel, and industrials as clients. As we complete 10 years of Tredence this year, we are on the cusp of an ambitious and exciting phase of expansion and growth. Tredence recently closed a USD 175 million Series B , which will help us build on growth momentum, strengthen vertical capabilities, and reach a broader customer base. Apart from our geographic footprint in the US, Canada & UK, we plan to open offices in Kolkata and a few tier 2 cities in India. In 2023, we also plan to hire more than 1000 employees across markets. Tredence is a (GPTW) certified company that values its employees and creates a positive work culture by providing opportunities for professional development and promoting work-life balance. At Tredence, nothing is impossible; we believe in pushing ourselves to limitless possibilities and staying true to our tagline, This position requires someone with good problem solving, business understanding and client presence. Overall professional experience of the candidate should be atleast 5 years with a maximum experience upto 15 years. The candidate must understand the usage of data Engineering tools for solving business problems and help clients in their data journey. Must have knowledge of emerging technologies used in companies for data management including data governance, data quality, security, data integration, processing, and provisioning. The candidate must possess required soft skills to work with teams and lead medium to large teams. Candidate should be comfortable with taking leadership roles, in client projects, pre-sales/consulting, solutioning, business development conversations, execution on data engineering projects. Role Description: Developing Modern Data Warehouse solutions using Databricks and Azure Stack Ability to provide solutions that are forward-thinking in data engineering and analytics space Collaborate with DW/BI leads to understand new ETL pipeline development requirements. Triage issues to find gaps in existing pipelines and fix the issues Work with business to understand the need in reporting layer and develop data model to fulfill reporting needs Drive technical discussion with client architect and team members Orchestrate the data pipelines in scheduler via Airflow Skills and Qualifications: Bachelor's and/or master's degree in computer science or equivalent experience. Good understanding of Databricks Data & AI platform and Databricks Delta Lake Architecture Should have hands-on experience in SQL, Python and Spark (PySpark) Experience in building ETL / data warehouse transformation processes Proficiency in RDBMS, complex SQL, PL/SQL, Unix Shell Scripting, performance tuning and troubleshoot Databricks Certified Data Engineer Associate/Professional Certification (Desirable). Comfortable working in a dynamic, fast-paced, innovative environment with several ongoing concurrent projects Should have experience working in Agile methodology Strong verbal and written communication skills. Strong analytical and problem-solving skills with a high attention to detail. Mandatory Skills Azure Databricks, Pyspark, Azure Data Factory, Azure Data Lake. Job Location - Bangalore, Chennai, Gurgaon, Pune, Kolkata Required Skills

Job Description We are seeking a highly skilled Azure Data Engineer with strong expertise in Data Architecture , PySpark/Python, Azure Databricks, and data streaming solutions . The ideal candidate will have hands-on experience in designing and implementing large-scale data pipelines, along with solid knowledge of data governance and data modeling . Key Responsibilities Design, develop, and optimize PySpark/Python-based data streaming jobs on Azure Databricks . Build scalable and efficient data pipelines for batch and real-time processing. Implement data governance policies, ensuring data quality, security, and compliance. Develop and maintain data models (dimensional, relational, NoSQL) to support analytics and reporting. Collaborate with cross-functional teams (data scientists, analysts, and business stakeholders) to deliver data solutions. Troubleshoot performance bottlenecks and optimize Spark jobs for efficiency. Ensure best practices in CI/CD, automation, and monitoring of data workflows. Mentor junior engineers and lead technical discussions (for senior/managerial roles). Mandatory Skills & Experience 5+ years of relevant experience as a Data Engineer/Analyst/Architect (8+ years for Manager/Lead positions). Expert-level proficiency in PySpark/Python and Azure Databricks (must have worked on real production projects ). Strong experience in building and optimizing streaming data pipelines (Kafka, Event Hubs, Delta Lake, etc.). 4+ years of hands-on experience in data governance & data modeling (ER, star schema, data vault, etc.). In-depth knowledge of Azure Data Factory, Synapse, ADLS, and SQL/NoSQL databases . Experience with Delta Lake, Databricks Workflows, and performance tuning . Familiarity with data security, metadata management, and lineage tracking . Excellent communication skills (must be able to articulate technical concepts clearly).

Looking for Data Engineers, immediate joiners only, for Hyderabad, Bengaluru and Noida Location. * Must have experience in Python, Kafka Stream, Pyspark, and Azure Databricks.* Role and responsibilities: Lead the design, development, and implementation of real-time data pipelines using Kafka, Python, and Azure Databricks . Architect scalable data streaming and processing solutions to support healthcare data workflows. Develop, optimize, and maintain ETL/ELT pipelines for structured and unstructured healthcare data. Ensure data integrity, security, and compliance with healthcare regulations (HIPAA, HITRUST, etc.). Collaborate with data engineers, analysts, and business stakeholders to understand requirements and translate them into technical solutions. Troubleshoot and optimize Kafka streaming applications, Python scripts, and Databricks workflows . Mentor junior engineers, conduct code reviews, and ensure best practices in data engineering . Stay updated with the latest cloud technologies, big data frameworks, and industry trends . Preferred candidate profile : 5+ years of experience in data engineering, with strong proficiency in Kafka and Python . Expertise in Kafka Streams, Kafka Connect, and Schema Registry for real-time data processing. Experience with Azure Databricks (or willingness to learn and adopt it quickly). Hands-on experience with cloud platforms (Azure preferred, AWS or GCP is a plus) . Proficiency in SQL, NoSQL databases, and data modeling for big data processing. Knowledge of containerization (Docker, Kubernetes) and CI/CD pipelines for data applications. Experience working with healthcare data (EHR, claims, HL7, FHIR, etc.) is a plus. Strong analytical skills, problem-solving mindset, and ability to lead complex data projects. Excellent communication and stakeholder management skills. Interested, call: Rose (9873538143 / WA : 8595800635) rose2hiresquad@gmail.com

Role Purpose Consultants are expected to complete specific tasks as part of a consulting project with minimal supervision. They will start to build a core areas of expertise and will contribute to client projects typically involving in-depth analysis, research, supporting solution development and being a successful communicator. The Consultant must achieve high personal billability. Responsibilities As aDeveloper, Analyze, design and develop components, tools and custom features using Databricks and streamsets as per business needs. Analyze, create and develop technical design to determine business functional and non-functional requirements & processes and review them with the technology leads and architects. Work collaboratively with all the teams as required to build a data model and setup things in Databricks andstreamsets as appropriate to transform the data and transfer it as appropriate. Develop solutions to publish/subscribe Kafka topics.

Role & responsibilities : Job Description: Primarily looking for a Data Engineer (AWS) with expertise in processing data pipelines using Data bricks, PySpark SQL on Cloud distributions like AWS Must have AWS Data bricks ,Good-to-have PySpark, Snowflake, Talend Requirements- • Candidate must be experienced working in projects involving • Other ideal qualifications include experiences in • Primarily looking for a data engineer with expertise in processing data pipelines using Databricks Spark SQL on Hadoop distributions like AWS EMR Data bricks Cloudera etc. • Should be very proficient in doing large scale data operations using Databricks and overall very comfortable using Python • Familiarity with AWS compute storage and IAM concepts • Experience in working with S3 Data Lake as the storage tier • Any ETL background Talend AWS Glue etc. is a plus but not required • Cloud Warehouse experience Snowflake etc. is a huge plus • Carefully evaluates alternative risks and solutions before taking action. • Optimizes the use of all available resources • Develops solutions to meet business needs that reflect a clear understanding of the objectives practices and procedures of the corporation department and business unit • Skills • Hands on experience on Databricks Spark SQL AWS Cloud platform especially S3 EMR Databricks Cloudera etc. • Experience on Shell scripting • Exceptionally strong analytical and problem-solving skills • Relevant experience with ETL methods and with retrieving data from dimensional data models and data warehouses • Strong experience with relational databases and data access methods especially SQL • Excellent collaboration and cross functional leadership skills • Excellent communication skills both written and verbal • Ability to manage multiple initiatives and priorities in a fast-paced collaborative environment • Ability to leverage data assets to respond to complex questions that require timely answers • has working knowledge on migrating relational and dimensional databases on AWS Cloud platform Skills Mandatory Skills: Apache Spark, Databricks, Java, Python, Scala, Spark SQL. Note : Need only Immediate joiners/ Serving notice period. Interested candidates can apply. Regards, HR Manager

We are looking for a skilled Azure Data Engineer to design, develop, optimize data pipelines for following 1, SQL+ETL+AZURE+Python+Pyspark+Databricks 2, SQL+ADF+ Azure 3, SQL+Python+Pyspark - Strong proficiency in SQL for data manipulation querying Required Candidate profile - Python and PySpark for data engineering tasks. - Exp with Databricks for big data processing analytics. - Knowledge of data modeling, warehousing, governance. - CI/CD pipelines for data deployment. Perks and benefits Perks and Benefits

About the role As a Technology Consulting, you will be a key member of the teams working on end-to-end AI and analytics solutions being built for our clients. While your primary focus will be on the data engineering and application engineering components of the overall solution, you will collaborate with internal data science teams for the ML aspects. As the person responsible for the overall success of the program, you will: Collaborate with cross-functional teams to optimize data engineering processes. Drive problem discovery, scoping, program management, delivery, etc. Lead requirements elicitation using a combination of business acumen and technology understanding Lead stakeholder communication and drive continuous improvement initiatives. Manage RFP (Request for Proposal) and SOW (Statement of Work) processes, ensuring accurate scoping and delivery commitments. Translate the requirements of the solution to technical architects. Review the solution design & estimation for conformity with client requirements Coordinate program delivery (communicating updates, bottlenecks, risks, delays, etc) Measure and articulate the value of solutions developed to help drive solution adoption by business teams. Provide technical consulting on data strategy and business intelligence initiatives. Ensure smooth integration of cloud technologies within enterprise systems. Design and implement ETL workflows, data pipelines, and warehousing solutions. Architect cloud-based data solutions using Azure, AWS, or GCP. Provide strategic guidance on ETL processes, data engineering solutions, and cloud architectures (Azure, AWS, GCP). Desired Skills and Experience: Technology Consulting Proven ability to lead engagements and advise on digital transformation. RFP & SOW Proficiency in managing proposal and contract negotiations. Stakeholder Management Excellent communication skills for cross-team collaboration. ETL & Data Engineering Strong expertise in data pipelines, warehousing, and transformations. Cloud Solutions – Experience with Azure, AWS, or GCP for scalable deployments.

About the Role: Grade Level (for internal use): 11 S&P Global EDO The Role: Lead- Software Engineering IT- Application Development. Join Our Team: Step into a dynamic team at the cutting edge of data innovation! Youll collaborate daily with talented professionals from around the world, designing and developing next-generation data products for our clients. Our team thrives on a diverse toolkit that evolves with emerging technologies, offering you the chance to work in a vibrant, global environment that fosters creativity and teamwork. The Impact: As a Lead Software Developer at S&P Global, youll be a driving force in shaping the future of our data products. Your expertise will streamline software development and deployment, aligning cutting-edge solutions with business needs. By ensuring seamless integration and continuous delivery, youll enhance product capabilities, delivering high-quality systems that meet the highest standards of availability, security, and performance. Your work will empower our clients with impactful, data-driven solutions, making a real difference in the financial world. Whats in it for You: Career Development: Build a rewarding career with a global leader in financial information and analytics, supported by continuous learning and a clear path to advancement. Dynamic Work Environment: Thrive in a fast-paced, forward-thinking setting where your ideas fuel innovation and your contributions shape groundbreaking solutions. Skill Enhancement: Elevate your expertise on an enterprise-level platform, mastering the latest tools and techniques in software development. Versatile Experience: Dive into full-stack development with hands-on exposure to cloud computing, Bigdata, and revolutionary GenAI technologies. Leadership Opportunities: Guide and inspire a skilled team, steering the direction of our products and leaving your mark on the future of technology at S&P Global. Responsibilities: Architect and develop scalable Bigdata and cloud applications, harnessing a range of cloud services to create robust, high-performing solutions. Design and implement advanced CI/CD pipelines, automating software delivery for fast, reliable deployments that keep us ahead of the curve. Tackle complex challenges head-on, troubleshooting and resolving issues to ensure our products run flawlessly for clients. Lead by example, providing technical guidance and mentoring to your team, driving innovation and embracing new processes. Deliver top-tier code and detailed system design documents, setting the standard with technical walkthroughs that inspire excellence. Bridge the gap between technical and non-technical stakeholders, turning complex requirements into elegant, actionable solutions. Mentor junior developers, nurturing their growth and helping them build skills and careers under your leadership. What Were Looking For: Were seeking a passionate, experienced professional with: 10-13 years of hands-on experience designing and building data-intensive solutions using distributed computing, showcasing your mastery of scalable architectures. Proven success implementing and maintaining enterprise search solutions in large-scale environments, ensuring peak performance and reliability. A history of partnering with business stakeholders and users to shape research directions and craft robust, maintainable products. Extensive experience deploying data engineering solutions in public clouds like AWS, GCP, or Azure, leveraging cloud power to its fullest. Advanced programming skills in Python, Java, .NET or Scala, backed by a portfolio of impressive projects. Strong knowledge of Gen AI tools (e.g., GitHub Copilot, ChatGPT, Claude, or Gemini) and their power to boost developer productivity. Expertise in containerization, scripting, cloud platforms, and CI/CD practices, ready to shine in a modern development ecosystem. 5+ years working with Python, Java, .NET, Kubernetes, and data/workflow orchestration tools, proving your technical versatility. Deep experience with SQL, NoSQL, Apache Spark, Airflow, or similar tools, operationalizing data-driven pipelines for large-scale batch and stream processing. A knack for rapid prototyping and iteration, delivering high-quality solutions under tight deadlines. Outstanding communication and documentation skills, adept at explaining complex ideas to technical and non-technical audiences alike. Take the Next Step: Ready to elevate your career and make a lasting impact in data and technologyJoin us at S&P Global and help shape the future of financial information and analytics. Apply today! Return to Work Have you taken time out for caring responsibilities and are now looking to return to workAs part of our Return-to-Work initiative (link to career site page when available), we are encouraging enthusiastic and talented returners to apply and will actively support your return to the workplace.

About the Role: Grade Level (for internal use): 10 Position summary Our proprietary software-as-a-service helps automotive dealerships and sales teams better understand and predict exactly which customers are ready to buy, the reasons why, and the key offers and incentives most likely to close the sale. Its micro-marketing engine then delivers the right message at the right time to those customers, ensuring higher conversion rates and a stronger ROI. What You'll Do You will be part of our Data Platform & Product Insights data engineering team. As part of this agile team, you will work in our cloud native environment to Build & support data ingestion and processing pipelines in cloud. This will entail extraction, load and transformation of big data from a wide variety of sources, both batch & streaming, using latest data frameworks and technologies Partner with product team to assemble large, complex data sets that meet functional and non-functional business requirements, ensure build out of Data Dictionaries/Data Catalogue and detailed documentation and knowledge around these data assets, metrics and KPIs. Warehouse this data, build data marts, data aggregations, metrics, KPIs, business logic that leads to actionable insights into our product efficacy, marketing platform, customer behaviour, retention etc. Build real-time monitoring dashboards and alerting systems. Coach and mentor other team members. Who you are 6+ years of experience in Big Data and Data Engineering. Strong knowledge of advanced SQL, data warehousing concepts and DataMart designing. Have strong programming skills in SQL, Python/ PySpark etc. Experience in design and development of data pipeline, ETL/ELT process on-premises/cloud. Experience in one of the Cloud providers GCP, Azure, AWS. Experience with relational SQL and NoSQL databases, including Postgres and MongoDB. Experience workflow management toolsAirflow, AWS data pipeline, Google Cloud Composer etc. Experience with Distributed Versioning Control environments such as GIT, Azure DevOps Building Docker images and fetch/promote and deploy to Production. Integrate Docker container orchestration framework using Kubernetes by creating pods, config Maps, deployments using terraform. Should be able to convert business queries into technical documentation. Strong problem solving and communication skills. Bachelors or an advanced degree in Computer Science or related engineering discipline. Good to have some exposure to Exposure to any Business Intelligence (BI) tools like Tableau, Dundas, Power BI etc. Agile software development methodologies. Working in multi-functional, multi-location teams Grade10 LocationGurugram Hybrid Modeltwice a week work from office Shift Time12 pm to 9 pm IST What You'll Love About Us Do ask us about these! Total Rewards. Monetary, beneficial and developmental rewards! Work Life Balance. You can't do a good job if your job is all you do! Prepare for the Future. Academy we are all learners; we are all teachers! Employee Assistance Program. Confidential and Professional Counselling and Consulting. Diversity & Inclusion. HeForShe! Internal Mobility. Grow with us! About automotiveMastermind Who we are: Founded in 2012, automotiveMastermind is a leading provider of predictive analytics and marketing automation solutions for the automotive industry and believes that technology can transform data, revealing key customer insights to accurately predict automotive sales. Through its proprietary automated sales and marketing platform, Mastermind, the company empowers dealers to close more deals by predicting future buyers and consistently marketing to them. automotiveMastermind is headquartered in New York City. For more information, visit automotivemastermind.com. At automotiveMastermind, we thrive on high energy at high speed. Were an organization in hyper-growth mode and have a fast-paced culture to match. Our highly engaged teams feel passionately about both our product and our people. This passion is what continues to motivate and challenge our teams to be best-in-class. Our cultural values of Drive and Help have been at the core of what we do, and how we have built our culture through the years. This cultural framework inspires a passion for success while collaborating to win. What we do: Through our proprietary automated sales and marketing platform, Mastermind, we empower dealers to close more deals by predicting future buyers and consistently marketing to them. In short, we help automotive dealerships generate success in their loyalty, service, and conquest portfolios through a combination of turnkey predictive analytics, proactive marketing, and dedicated consultative services. 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

Core Competences Required and Desired Attributes: Bachelor's degree in computer science, Information Technology, or a related field. Proficiency in Azure Data Factory, Azure Databricks and Unity Catalog, Azure SQL Database, and other Azure data services. Strong programming skills in SQL, Python and PySpark languages. Experience in the Asset Management domain would be preferable. Strong proficiency in data analysis and data modelling, with the ability to extract insights from complex data sets. Hands-on experience in Power BI, including creating custom visuals, DAX expressions, and data modelling. Familiarity with Azure Analysis Services, data modelling techniques, and optimization. Experience with data quality and data governance frameworks with an ability to debug, fine tune and optimise large scale data processing jobs. Strong analytical and problem-solving skills, with a keen eye for detail. Excellent communication and interpersonal skills, with the ability to work collaboratively in a team environment. Proactive and self-motivated, with the ability to manage multiple tasks and deliver high-quality results within deadlines. Roles and Responsibilities Core Competences Required and Desired Attributes: Bachelor's degree in computer science, Information Technology, or a related field. Proficiency in Azure Data Factory, Azure Databricks and Unity Catalog, Azure SQL Database, and other Azure data services. Strong programming skills in SQL, Python and PySpark languages. Experience in the Asset Management domain would be preferable. Strong proficiency in data analysis and data modelling, with the ability to extract insights from complex data sets. Hands-on experience in Power BI, including creating custom visuals, DAX expressions, and data modelling. Familiarity with Azure Analysis Services, data modelling techniques, and optimization. Experience with data quality and data governance frameworks with an ability to debug, fine tune and optimise large scale data processing jobs. Strong analytical and problem-solving skills, with a keen eye for detail. Excellent communication and interpersonal skills, with the ability to work collaboratively in a team environment. Proactive and self-motivated, with the ability to manage multiple tasks and deliver high-quality results within deadlines.

We are seeking a seasoned Engineering Manager (Data Engineering) to lead the end-to-end management of enterprise data assets and operational data workflows. This role is critical in ensuring the availability, quality, consistency, and timeliness of data across platforms and functions, supporting analytics, reporting, compliance, and digital transformation initiatives. You will be responsible for the day-to-day data operations, manage a team of data professionals, and drive process excellence in data intake, transformation, validation, and delivery. You will work closely with cross-functional teams including data engineering, analytics, IT, governance, and business stakeholders to align operational data capabilities with enterprise needs. Roles & Responsibilities: Lead and manage the enterprise data operations team, responsible for data ingestion, processing, validation, quality control, and publishing to various downstream systems. Define and implement standard operating procedures for data lifecycle management, ensuring accuracy, completeness, and integrity of critical data assets. Oversee and continuously improve daily operational workflows, including scheduling, monitoring, and troubleshooting data jobs across cloud and on-premise environments. Establish and track key data operations metrics (SLAs, throughput, latency, data quality, incident resolution) and drive continuous improvements. Partner with data engineering and platform teams to optimize pipelines, support new data integrations, and ensure scalability and resilience of operational data flows. Collaborate with data governance, compliance, and security teams to maintain regulatory compliance, data privacy, and access controls. Serve as the primary escalation point for data incidents and outages, ensuring rapid response and root cause analysis. Build strong relationships with business and analytics teams to understand data consumption patterns, prioritize operational needs, and align with business objectives. Drive adoption of best practices for documentation, metadata, lineage, and change management across data operations processes. Mentor and develop a high-performing team of data operations analysts and leads. Functional Skills: Must-Have Skills: Experience managing a team of data engineers in biotech/pharma domain companies. Experience in designing and maintaining data pipelines and analytics solutions that extract, transform, and load data from multiple source systems. Demonstrated hands-on experience with cloud platforms (AWS) and the ability to architect cost-effective and scalable data solutions. Experience managing data workflows in cloud environments such as AWS, Azure, or GCP. Strong problem-solving skills with the ability to analyze complex data flow issues and implement sustainable solutions. Working knowledge of SQL, Python, or scripting languages for process monitoring and automation. Experience collaborating with data engineering, analytics, IT operations, and business teams in a matrixed organization. Familiarity with data governance, metadata management, access control, and regulatory requirements (e.g., GDPR, HIPAA, SOX). Excellent leadership, communication, and stakeholder engagement skills. Well versed with full stack development & DataOps automation, logging frameworks, and pipeline orchestration tools. Strong analytical and problem-solving skills to address complex data challenges. Effective communication and interpersonal skills to collaborate with cross-functional teams. Good-to-Have Skills: Data Engineering Management experience in Biotech/Life Sciences/Pharma Experience using graph databases such as Stardog or Marklogic or Neo4J or Allegrograph, etc. Education and Professional Certifications Doctorate Degree with 3-5 + years of experience in Computer Science, IT or related field OR Masters degree with 6 - 8 + years of experience in Computer Science, IT or related field OR Bachelors degree with 10 - 12 + years of experience in Computer Science, IT or related field AWS Certified Data Engineer preferred Databricks Certificate preferred Scaled Agile SAFe certification preferred Soft Skills: Excellent analytical and troubleshooting skills Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation Ability to manage multiple priorities successfully Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills

What you will do In this vital role you will responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives, and visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes. Roles & Responsibilities: Design, develop, and maintain data solutions for data generation, collection, and processing. Be a key team member that assists in the design and development of the data pipeline. Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems. Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions. Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks. Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs. Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency. Implement data security and privacy measures to protect sensitive data. Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions. Collaborate and communicate effectively with product teams. What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications and Experience Masters degree and 1 to 3 years of experience in Computer Science, IT, or related field OR Bachelors degree and 3 to 5 years of experience in Computer Science, IT, or related field OR Diploma and 7 to 9 years of experience in Computer Science, IT, or related field Must-Have Skills: Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing. Proficiency in data analysis tools (e.g., SQL) and experience with data visualization tools. Excellent problem-solving skills and the ability to work with large, complex datasets. Preferred Qualifications: Good-to-Have Skills: Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development. Strong understanding of data modeling, data warehousing, and data integration concepts. Knowledge of Python/R, Databricks, SageMaker, cloud data platforms. Professional Certifications: Certified Data Engineer / Data Analyst (preferred on Databricks or cloud environments). Certified Data Scientist (preferred on Databricks or Cloud environments). Machine Learning Certification (preferred on Databricks or Cloud environments). Soft Skills: Excellent critical-thinking and problem-solving skills. Strong communication and collaboration skills. Demonstrated awareness of how to function in a team setting. Demonstrated presentation skills.

Role Purpose The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters Do 1. Instrumental in understanding the requirements and design of the product/ software Develop software solutions by studying information needs, studying systems flow, data usage and work processes Investigating problem areas followed by the software development life cycle Facilitate root cause analysis of the system issues and problem statement Identify ideas to improve system performance and impact availability Analyze client requirements and convert requirements to feasible design Collaborate with functional teams or systems analysts who carry out the detailed investigation into software requirements Conferring with project managers to obtain information on software capabilities 2. Perform coding and ensure optimal software/ module development Determine operational feasibility by evaluating analysis, problem definition, requirements, software development and proposed software Develop and automate processes for software validation by setting up and designing test cases/scenarios/usage cases, and executing these cases Modifying software to fix errors, adapt it to new hardware, improve its performance, or upgrade interfaces. Analyzing information to recommend and plan the installation of new systems or modifications of an existing system Ensuring that code is error free or has no bugs and test failure Preparing reports on programming project specifications, activities and status Ensure all the codes are raised as per the norm defined for project / program / account with clear description and replication patterns Compile timely, comprehensive and accurate documentation and reports as requested Coordinating with the team on daily project status and progress and documenting it Providing feedback on usability and serviceability, trace the result to quality risk and report it to concerned stakeholders 3. Status Reporting and Customer Focus on an ongoing basis with respect to project and its execution Capturing all the requirements and clarifications from the client for better quality work Taking feedback on the regular basis to ensure smooth and on time delivery Participating in continuing education and training to remain current on best practices, learn new programming languages, and better assist other team members. Consulting with engineering staff to evaluate software-hardware interfaces and develop specifications and performance requirements Document and demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code Documenting very necessary details and reports in a formal way for proper understanding of software from client proposal to implementation Ensure good quality of interaction with customer w.r.t. e-mail content, fault report tracking, voice calls, business etiquette etc Timely Response to customer requests and no instances of complaints either internally or externally Deliver No. Performance Parameter Measure 1. Continuous Integration, Deployment & Monitoring of Software 100% error free on boarding & implementation, throughput %, Adherence to the schedule/ release plan 2. Quality & CSAT On-Time Delivery, Manage software, Troubleshoot queries,Customer experience, completion of assigned certifications for skill upgradation 3. MIS & Reporting 100% on time MIS & report generation Mandatory Skills: Python for Insights.

Role Purpose The purpose of this role is to design, test and maintain software programs for operating systems or applications which needs to be deployed at a client end and ensure its meet 100% quality assurance parameters Do 1. Instrumental in understanding the requirements and design of the product/ software Develop software solutions by studying information needs, studying systems flow, data usage and work processes Investigating problem areas followed by the software development life cycle Facilitate root cause analysis of the system issues and problem statement Identify ideas to improve system performance and impact availability Analyze client requirements and convert requirements to feasible design Collaborate with functional teams or systems analysts who carry out the detailed investigation into software requirements Conferring with project managers to obtain information on software capabilities 2. Perform coding and ensure optimal software/ module development Determine operational feasibility by evaluating analysis, problem definition, requirements, software development and proposed software Develop and automate processes for software validation by setting up and designing test cases/scenarios/usage cases, and executing these cases Modifying software to fix errors, adapt it to new hardware, improve its performance, or upgrade interfaces. Analyzing information to recommend and plan the installation of new systems or modifications of an existing system Ensuring that code is error free or has no bugs and test failure Preparing reports on programming project specifications, activities and status Ensure all the codes are raised as per the norm defined for project / program / account with clear description and replication patterns Compile timely, comprehensive and accurate documentation and reports as requested Coordinating with the team on daily project status and progress and documenting it Providing feedback on usability and serviceability, trace the result to quality risk and report it to concerned stakeholders 3. Status Reporting and Customer Focus on an ongoing basis with respect to project and its execution Capturing all the requirements and clarifications from the client for better quality work Taking feedback on the regular basis to ensure smooth and on time delivery Participating in continuing education and training to remain current on best practices, learn new programming languages, and better assist other team members. Consulting with engineering staff to evaluate software-hardware interfaces and develop specifications and performance requirements Document and demonstrate solutions by developing documentation, flowcharts, layouts, diagrams, charts, code comments and clear code Documenting very necessary details and reports in a formal way for proper understanding of software from client proposal to implementation Ensure good quality of interaction with customer w.r.t. e-mail content, fault report tracking, voice calls, business etiquette etc Timely Response to customer requests and no instances of complaints either internally or externally Deliver No. Performance Parameter Measure 1. Continuous Integration, Deployment & Monitoring of Software 100% error free on boarding & implementation, throughput %, Adherence to the schedule/ release plan 2. Quality & CSAT On-Time Delivery, Manage software, Troubleshoot queries,Customer experience, completion of assigned certifications for skill upgradation 3. MIS & Reporting 100% on time MIS & report generation Mandatory Skills: DataBricks - Data Engineering.

Role Overview We are looking for a Senior ETL Engineer with deep expertise in Apache Airflow to design, build, and manage complex data workflows and pipelines across cloud platforms. The ideal candidate will bring strong experience in Python, SQL, and cloud-native tools (AWS/GCP) to deliver scalable and reliable data infrastructure, supporting analytics, reporting, and operational systems. Key Responsibilities Design, implement, and optimize scalable ETL/ELT workflows using Apache Airflow DAGs . Build and maintain data pipelines with Python and SQL , integrating multiple data sources. Develop robust solutions for pipeline orchestration, failure recovery, retries , and notifications. Leverage AWS or GCP services (e.g., S3, Lambda, BigQuery, Cloud Functions, IAM). Integrate with internal and external data systems via secure REST APIs and Webhooks . Monitor Airflow performance, manage DAG scheduling, and resolve operational issues. Implement observability features like logging, metrics, alerts, and pipeline health checks. Collaborate with analytics, data science, and engineering teams to support data needs. Drive automation and reusability across pipeline frameworks and templates. Ensure data quality, governance, compliance , and lineage across ETL processes. Required Skills 5+ years of experience in ETL/Data Engineering with hands-on Airflow expertise. Strong programming skills in Python , with solid experience writing production scripts. Proficiency in SQL for data manipulation, joins, and performance tuning. Deep knowledge of Apache Airflow scheduling, sensors, operators, XComs, and hooks. Experience working on cloud platforms like AWS or GCP in data-heavy environments. Comfort with REST APIs , authentication protocols, and data integration techniques. Knowledge of CI/CD tools, Git, and containerization (Docker, Kubernetes). Nice to Have Familiarity with dbt, Snowflake, Redshift, BigQuery, or other modern data platforms. Experience with Terraform or infrastructure-as-code for Airflow deployment. Understanding of data privacy, regulatory compliance (GDPR, HIPAA), and metadata tracking.