Data Engineer

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…