Data Engineer at MerQube Inc

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

08 Apr, 26

Salary

0.0

Posted On

08 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, AWS, ETL, Python, SQL, Data Modeling, Data Lakes, Data Governance, Data Quality, Financial Data, Cloud Platforms, Data Pipelines, Batch Processing, Streaming Technologies, Data Catalogs, Collaboration

Industry

Capital Markets

Description

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, etc.) Experience building data catalogs, governance layers, or migrating legacy pipelines to cloud-native architectures Exposure to containerized environments (Docker, Kubernetes) and modern data warehouses (Redshift, Snowflake, BigQuery, etc.) Why join MerQube? We believe in creating an environment where engineers thrive, innovate, and grow. We are proud to offer: Competitive compensation packages and Comprehensive benefits Flexible working arrangements collaborative, community-first culture Strong Focus on health, wellness, and work-life balance Opportunities to make real impact in fast-scaling fintech platform Equal Opportunity Employer MerQube is committed to building a diverse and inclusive workplace. All qualified applicants will be considered without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status, or any other legally protected characteristic. If you’re passionate about building world-class data systems and want to shape the future of indexing technology, we’d love to have you onboard.

Responsibilities

The Data Engineer will design, build, and maintain large-scale ETL/ELT pipelines and modernize legacy ETL frameworks into standardized AWS pipelines. They will also collaborate with various teams to support index construction and analytics for global clients.