Senior Data Engineer [T500-29515]

FM; Bengaluru; On-site; INR 700,000 - 1,100,000; Full time

Job summary

FM India is seeking a data-focused professional to perform data acquisition, modelling, and pipeline design. You will work on structured and unstructured sources across underwriting, risk, client service, and sales domains, ensuring high data quality and reliable data delivery.

You will collaborate with data teams to build scalable data infrastructure using SQL Server, Synapse, and Azure services, while supporting analytics, reporting, and production readiness.

Qualifications

• Requires 2 years of experience in data engineering/data analytics.
• Proficient in data modeling and understanding of relational 3rd normal form.
• Knowledge of Azure cloud applications and data warehousing concepts.
• Proficiency with SQL, Spark, PySpark, and ETL processes.

Responsibilities

• Analyze data sources across product journeys (Underwriting, Risk, Client Service, Sales, Marketing, Claims).
• Develop data models and data flows; design and optimize ETL/ELT pipelines.
• Ensure data quality, security, and compliance; support data exploration and production issues.
• Collaborate with data engineers, analysts, scientists, and stakeholders to meet reporting needs.

Skills

SQL

Spark/PySpark

ETL

Data modeling

Azure Cloud

Tools

SQL Server

Massively Parallel Processing (MPP)

Synapse

Fabric

Job description

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.

Position Summary:

Responsible for analysis, data modeling, data collection, data integration, and preparation of data for consumption. This includes creating and managing data infrastructure, data pipeline design, implementation and data verification. Along with the team, responsible for ensuring the highest standards of data quality, security and compliance. Displays personal accountability for successful outcomes and support quality efforts within the team. Interfaces with colleagues and other stakeholders to evaluate defined business requirements and processes. Uses available approved technologies. Responsible for implementing methods to improve data reliability and quality, combine raw information from different sources to create consistent data sets. This role will need to be well versed in DataOps and have learned, and are capable of using, relevant technologies. Those holding this position are typically assigned to lead small scale projects and participate as part of a development team on larger projects.

Job Responsibilities:

Data Acquisition:

• Develop solid knowledge of structured and unstructured data sources within each product journey (Underwriting and Risk; Client Service, Sales and Marketing; Claims; Account and Location Engineering) as well as emerging data sources (purchased data sets; external data; tc.)
• Partner with Data Analytics team members, product owners, developers, solution architects, business analysts, data engineers, data analysts, data scientists and others to understand data and reporting needs
• Develop solutions using data modeling techniques
• Use technologies such as Analytical Platform Services (APS), Synapse, SQL Server, SSIS, 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:

• Data flow, infrastructure pipelines, ETL/ELT, structured and unstructured
• data movement and storage solutions.
• 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.

Support data exploration and transformation needs:

• Support team members with data cleansing tasks
• Conduct data profiling to identify data anomalies
• Assist team members with data preparation tasks
• Support users and production applications
• Support developers, data analysts and data scientists who need to interact
• with data in either data warehouse
• Analyze and assess reported data quality issues, quickly identifying root
• Consult dba(s) and team members on configuration and maintenance of the
• warehouse infrastructure
• Monitor system performance and identify opportunities for optimization
• Monitor storage capacity and reliability
• Address production issues quickly, with appropriate validation and deployment steps
• Provide clear and professional communication to users, management, and teammates
• Provide ad hoc data extracts and analysis to respond to tactical business needs.

Participate in effective execution of team priorities:

• Identify work tasks and capture them in the team backlog
• Organize known tasks, following provided prioritization
• Provide production support
• Network with product teams to keep abreast of database changes as well as business process changes which result in data interpretation changes.

Skill and Experience:

• 2 year of experience required to perform essential job functions.
• Data modeling abilities
• Relational 3rd Normal Form and nonrelational KimballInmon database theory
• Design, build, maintain data warehouses
• Understanding of database clustering
• Experience with databases including SQL Server and Massively Parallel Processing mpp
• Knowledge of Azure Cloud applications
• Programming languages C, Python, RScript, JSON, Java

Must Have Skills:

Required: SQL, Spark/Pyspark, ETL, Fabric, Data Lakes/Warehouses, ability to read and create data models; Preferred: Python, Kafka, Synapse.