Data Engineer

• Develop working knowledge of structured data sources within each product journey (Underwriting and Risk; Client Service, Sales and Marketing; Claims; Account and Location Engineering).
• Partner with Data Analytics team members, developers, solution architects, business analysts, data engineers, data analysts, data scientists to understand data and reporting needs.
• Create and use data models as a means toward developing and documenting code.
• Learn technologies such as Fabric Platform, Synapse Analytics Platform, Azure services, Kafka and others as required
• Validate code through detailed and disciplined testing.
• Participate in peer code review to ensure solutions are accurate .
• Ensure tables and views are designed for data integrity, efficiency and performance, and are easy to comprehend.

• Contribute to the design, development, and maintenance of data pipelines and integrations for structured and unstructured data sources across enterprise product domains (e.g., Underwriting, Risk, Claims, Client Services, Sales and Marketing), working under the guidance of senior engineers.
• Develop and support ETL/ELT solutions using approved cloud and analytics platforms (e.g., Synapse, SQL Server, Azure services such as Data Factory, Fabric, and data lakes), following established architectures, standards, and best practices.
• Apply standard testing practices and participate in peer reviews to help ensure data solutions meet expectations for accuracy, performance, scalability, and maintainability, with coaching and feedback from more experienced team members.
• Implement defined data flows and infrastructure pipelines to support the movement and storage of structured and unstructured data into and out of Data Analytics data assets, adhering to documented designs and operational procedures.
• Design data models and data flows into and out of Data Analytics databases.
• Understand and design data relationships between business and data subject areas.
• Follow standards for naming conventions, code documentation and code review.

• Investigate reported data quality issues, helping identify root causes and assisting with fixes under guidance from senior team members.
• Assist with data profiling, cleansing, and transformation tasks in collaboration with analytics and business partners.
• Monitor data pipelines and systems for basic performance and reliability issues, escalating concerns and supporting optimization efforts.
• Help resolve production issues by following established validation, testing, and deployment procedures; provide routine production support.
• Work with DBAs and teammates to support warehouse configuration, maintenance, and day to day operations.
• Learn and apply foundational data modeling concepts, including understanding relationships between business and data subject areas.
• Follow established standards for naming conventions, documentation, version control, and code review.

• Collaborate with product owners, solution architects, business analysts, data analysts, data scientists, and other engineers to understand basic data and reporting requirements and help translate them into technical tasks.
• Assist with data exploration and transformation activities under guidance from senior team members.
• Support data cleansing efforts by helping identify and correct data issues.
• Perform data profiling to help surface data anomalies and quality concerns.
• Participate in hybrid agile delivery practices, including backlog refinement, task estimation, prioritization, and raising potential conflicts or risks.
• Assist with data preparation tasks for analytics, reporting, and modeling.
• Help support users and production data applications by responding to questions and troubleshooting issues.
• Support developers, data analysts, and data scientists who need to access and work with data in the data warehouse.
• Analyze reported data quality issues and assist in identifying potential root causes.
• Monitor system performance and escalate opportunities for optimization to senior engineers.
• Help monitor storage capacity and system reliability.
• Assist in resolving production issues by following established validation, testing, and deployment processes.
• Communicate clearly and professionally with users, teammates, and management.
• Provide ad hoc data extracts and basic analysis to support tactical business needs.

• Assist in identifying assigned work and documenting tasks in the team backlog, following established intake processes.
• Maintain and organize assigned tasks according to provided priorities and guidance from senior team members or leads.
• Communicate potential conflicts or competing priorities to a lead or manager in a timely manner.
• Support production data processes by helping investigate issues, performing routine checks, and escalating problems as needed.
• Collaborate with product and analytics partners to stay informed of documented database or business process changes that may impact data interpretation, under guidance from the team.

• 1 - 2 year of experience required to perform essential job functions.
• Working knowledge of SQL and relational database concepts, including basic normalization and dimensional modeling.
• Experience supporting or building data warehouses and/or data lakes.
• Familiarity with cloud-based data platforms and services (e.g., Fabric, Synapse Analytics, Azure services, Kafka).
• Programming experience using SQL and Python; exposure to structured and semi-structured data formats (e.g., JSON).
• Foundational understanding of DataOps concepts such as testing, deployment, monitoring, and operational support.
• Relational and nonrelational database theory.
• Knowledge of Azure Cloud applications.
• ETL/ELT pipeline design and build.
• Programming languages SQL, Python, Spark, Kafka, Azure, JSON.

• SQL.
• Python, Spark, Data lakes, Data warehouses.
• Fabric Platform.
• Ability to read and create data models.
• ETL/ELT Pipeline development experience.

• Preferred: Kafka, Synapse Analytics Platform.
• Relational (3NF) and non-relational (Inmon/Kimball) database theory.
• AI/LLM knowledge, experience preferred.
• Python.

FM India