Data Engineer

About the role

About MerQube

MerQube is a cutting-edge fintech firm specializing in the development of advanced technology for indexing and rules-based investing. Founded in 2019 by industry veterans and technology experts, MerQube provides a tech-focused alternative in the indexing space, with offices in New York, San Francisco, and London.

We design and calculate a wide variety of indices, including thematic, ESG, QIS, and delta one strategies, spanning multiple asset classes such as equities, futures, and options. Powered by modern cloud architecture and advanced index-tracking technology, our platform helps clients bring sophisticated ideas to market quickly, securely, and at scale.

Summary

Are you passionate about building robust, scalable data systems that power mission-critical financial platforms? Do you enjoy working hands-on with complex financial datasets, modern data pipelines, and governed data lakes?

We are looking for a Data Engineer to join our growing platform engineering team in Bangalore. You will play a key role in modernizing and scaling MerQube’s core market data and index computation platforms by transforming legacy ETL pipeline into standardized cloud-native AWS data platform.

What you’ll work on?

As part of the Platform Engineering team, you will design, build, and operate scalable AWS-based data pipelines and a resilient lakehouse platform serving both transactional and analytical workloads. Your work will directly support index construction, analytics, research, and reporting used by global clients.

Core responsibilities:

- Design, build, and maintain large-scale ETL/ELT pipelines to ingest, normalize, and curate market, reference, and vendor data

- Modernize legacy ETL frameworks into standardized, cloud-native AWS pipelines

- Build and manage data lakes and analytics-ready datasets using AWS-native services

- Clean, standardize, and govern financial instrument identifiers, mappings, corporate actions, and historical data across vendors

- Design canonical financial data models (facts, dimensions, hierarchies, and mappings)

- Implement data quality checks, lineage, observability, and validation frameworks to ensure accurate index calculations

- Develop data catalogs and inventory systems to improve data discoverability and governance

- Collaborate closely with Product, Index Operations, Research, and Engineering teams to translate financial logic into scalable data pipelines

- Monitor production data systems, troubleshoot issues, and support on-call rotations as needed

What the position requires

- Bachelor’s Degree in Computer Science, Engineering, Mathematics, or equivalent experience

- 4–7 years of experience as a Data Engineer, preferably in fintech, trading, market data, or financial analytics domains

- Strong programming skills in Python and solid SQL expertise