About the Role

As a Reference Data Engineer, you will design, build, and optimize data pipelines that acquire, transform, validate, and distribute critical financial reference data across business systems. You will play a key role in ensuring the accuracy, consistency, and availability of instrument, market, and counterparty data used in trading, risk, regulatory, and operational processes. Success in this role is measured by the reliability, scalability, and observability of data platforms, as well as the quality and timeliness of data delivered to downstream consumers.

You will collaborate closely with engineering, product, operations, and data stakeholders to drive continuous improvements in data architecture and governance.

What You Will Be Doing

- Design, develop, and maintain scalable backend services and data pipelines using Java as the primary backend programming language.
- Ingest, process, and integrate reference data from vendors, APIs, and internal platforms.
- Normalize identifiers and attributes across multiple sources to create trusted, canonical datasets.
- Implement automated data quality controls, validation frameworks, and reconciliation processes.
- Monitor pipeline performance, troubleshoot incidents, and drive root-cause resolution to improve reliability.
- Design and optimize relational database schemas, data models, and query performance.
- Build observable systems with robust logging, alerting, monitoring, and operational support capabilities.
- Manage end-to-end data lifecycle processes, including lineage, governance, auditing, and version control.
- Partner with cross-functional teams to define and implement scalable data interfaces and schema evolution strategies.




- Drive automation initiatives that improve data freshness, reduce manual intervention, and support operational excellence.

Required Qualifications

- Bachelors degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
- 6 to 11 years of software engineering experience, with strong expertise in Java backend development.
- Proven experience building and supporting enterprise-scale data processing systems and pipelines.
- Experience integrating third-party data vendors, APIs, and external data services.
- Solid knowledge of structured and semi-structured data formats, including JSON, XML, and CSV.
- Hands-on experience with relational databases such as PostgreSQL, including schema design, data modeling, and performance optimization.
- Experience implementing data validation, reconciliation, monitoring, and quality assurance frameworks.
- Strong understanding of software engineering best practices, including testing, code quality, CI/CD, and operational ownership.
- Excellent problem-solving, collaboration, and communication skills with a focus on delivering reliable production systems.

Preferred Qualifications

- Experience with Clojure and functional programming concepts.
- Familiarity with financial reference data domains, including instrument identifiers, market codes, legal entities, and counterparty data.
- Experience working with cloud platforms such as AWS or Microsoft Azure.
- Knowledge of distributed systems, event-driven architectures, and data integration patterns.
- Experience building highly available, resilient, and observable data platforms in regulated environments.
- Understanding of regulatory, risk, or capital markets data workflows.

📌 Data Engineer (Pune)
🏢 FIS
📍 Pune