Data Engineer T500-28480

Position: Data Engineer [T500-28480]
Location: Vasanthanagar

About us:

We are a highly successful 190-year-old, Fortune 500 commercial property insurance company of 6,000+ employees with a unique focus on science and risk engineering. Businesses worldwide trust our expertise to protect their assets, relying on our comprehensive risk assessments and robust, engineering-based insurance solutions to safeguard against fire, natural disasters, and other perils. Serving over a quarter of the Fortune 500 and major corporations globally, we deliver data-driven strategies that enhance resilience, ensure business continuity, and empower organizations to thrive.

FM India is a strategic location for driving our global operational efficiency. Our presence in India allows us to leverage the country’s talented workforce and advance our capabilities to serve our clients better. We have diverse corporate functions that emphasize research, advanced technologies like AI and analytics, risk engineering, research, finance, marketing, HR, etc. working together to provide innovative solutions and nurture lasting relationships – from co-workers to clients.

Role

Title:

Data Engineer

Position Summary:

The Data Engineer is a key role on the Data Analytics team. The Data Engineer is responsible for developing, maintaining, and supporting data pipelines, data models, and data assets that enable analytics, reporting, and downstream data consumption. This role focuses on implementing well defined data solutions using approved technologies, following established standards for data quality, security, and reliability. The Data Engineer is responsible for creating and managing data infrastructure, data pipeline design, implementation and data verification.

Along with the team, the Data Engineer is responsible for ensuring the highest standards of data quality, security and compliance. Additionally, the Data Engineer will implement methods to improve data reliability and quality, combine raw information from different sources to create consistent data sets. Incumbents are learning relevant technologies. Displays personal accountability for successful outcomes and support quality efforts within the team.

Receptive and responsive to mentoring from more senior team members on design and development techniques, enhancements, or support efforts. The Data Engineer will need to become versed in Data Ops, especially where Agile development, Dev Ops, and Continuous Improvement intersect. The Data Engineer I is the entry level position in the Data Engineer job family. Those holding this position are typically assigned to work as part of a project team.

Job Responsibilities:

Data Engineering & Development:
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.

Move and Store Data:
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…