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
- Hands-on experience building batch and/or streaming ETL pipelines
- Experience working with large, messy, heterogeneous datasets
- Strong understanding of data modeling concepts (fact/dimension models, canonical models, historical versioning)
- Experience with cloud platforms, preferably AWS (S3, Glue, Lambda, Step Functions, Athena/Redshift, CloudWatch, IAM)
- Familiarity with data orchestration tools such as Airflow or similar
Preferred Qualifications
- Experience with Spark or PySpark for large-scale data transformations
- Experience with streaming technologies such as Kafka or similar systems
- Experience working with financial market data providers (e.g., Bloomberg, Refinitiv, Morningstar, Nasdaq)
- Knowledge of financial instruments, corporate actions, and identifiers (ISIN, CUSIP, RIC, e