Job Summary

Job Title: Data Engineer. Position type: Full Time. Work Location: Bangalore. Working style: Hybrid. People Manager role: No. Required education and certifications critical for the role: Any Graduate or Post-Graduate (full time). Required years of experience: Minimum 4 years of relevant experience.

The Data Engineer will contribute to the Altair modernization program by developing and maintaining data pipelines on Azure and Databricks. You will work on building scalable data solutions that support reinsurance analytics, Property & Casualty loss ratio calculations, and workflow automation. As an individual contributor, you will collaborate with Senior Data Engineers, Solution Architects, Business Analysts, and domain SMEs to deliver reliable data assets.

This role offers an excellent opportunity to work on a large-scale modernization initiative, gain exposure to the reinsurance domain, and develop expertise in modern cloud data platforms and AI-enabled solutions.

Responsibilities

- Data Pipeline Development: Develop and maintain data ingestion, transformation, and integration pipelines on Databricks using PySpark. Build ETL/ELT workflows to process structured and unstructured data from multiple upstream systems. Implement data transformations following established design patterns and best practices. Support data imports using Unity Catalog and agreed ingestion patterns. Contribute to the development of data flows for the Altair modernization program.
- Data Quality & Governance: Implement data quality checks, validation processes, and error handling in data pipelines. Support data governance, security, lineage, and compliance standards. Develop and maintain data models and schemas for reinsurance business processes. Ensure data accuracy and reliability for downstream analytics and reporting.
- Business Requirements & Collaboration: Work with Business Analysts and SMEs to understand reinsurance business requirements.



Translate moderately complex business requirements into technical data solutions. Collaborate with Product Owners, Project Managers, and QA Engineers to deliver data assets. Participate in requirement gathering sessions and provide technical input.
- Technical Development & Best Practices: Write clean, maintainable, and well-documented code following team standards. Participate in code reviews and incorporate feedback to improve code quality. Contribute to the development of reusable components and data engineering patterns. Create technical documentation and operational procedures for data pipelines. Support & Optimization: Monitor data pipeline performance and reliability. Troubleshoot data issues and implement fixes in collaboration with senior team members. Support production data pipelines and respond to operational issues. Identify opportunities for pipeline optimization and performance improvement.
- Learning & Knowledge Transfer: Participate in knowledge transfer sessions with external vendors and senior team members. Learn about reinsurance domain concepts, business processes, and analytics requirements. Stay updated on Azure, Databricks, and data engineering best practices. Contribute to building in-house capabilities and reducing vendor dependency.

Requirements

- Education & Experience: Bachelors degree in Engineering, Computer Science, Data Engineering, Information Systems, or related field. 4 years of experience in data engineering, software engineering, or big data development. Experience developing ETL/ELT pipelines and working with large-scale datasets.




- Technical Skills: Solid proficiency in Python for data processing and engineering. Strong expertise in SQL for data manipulation and analysis. Experience with PySpark or willingness to learn and work with distributed data processing. Knowledge of Databricks or similar cloud data platforms. Understanding of Azure data services or other cloud platforms (AWS, GCP). Experience with ETL/ELT workflows and data integration. Understanding of data modeling and data quality principles. Familiarity with version control systems (Git) and CI/CD concepts.
- Business & Analytical Skills: Ability to understand and translate business requirements into technical solutions. Good analytical and problem-solving skills. Basic understanding of statistical concepts. Strong communication skills to collaborate with technical and non-technical stakeholders. Ability to work independently with guidance from senior team members. Eagerness to learn about new domains and technologies.

Preferred Qualifications

- Exposure to insurance, reinsurance, or financial services domains
- Familiarity with Unity Catalog for data governance
- Understanding of Property & Casualty insurance or loss ratio calculations
- Knowledge of business process management or workflow concepts
- Interest in AI/ML and experience with Azure OpenAI or LLM technologies
- Familiarity with microservices architecture and APIs
- Experience with workflow orchestration tools (Airflow, Azure Data Factory, etc.)
- Azure certifications or willingness to pursue certifications
- Exposure to Agile development methodologies
- Experience working in team-oriented, cross-functional teams

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Data Engineer (Bengaluru)
🏢 Aon
📍 Bengaluru