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MerQube

Index provider licensing cloud-based, rules-based indices

Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent experience is required.
  • Four to seven years of experience as a Data Engineer is required, preferably in fintech, trading, market data, or financial analytics.
  • Strong programming skills in Python and solid SQL expertise are required.
  • Hands-on experience building batch and/or streaming extract, transform, and load pipelines is required.
  • Experience working with large, messy, heterogeneous datasets is required.
  • Strong understanding of data modeling concepts, including fact/dimension models, canonical models, and historical versioning, is required.
  • Experience with cloud platforms, preferably Amazon Web Services, including S3, Glue, Lambda, Step Functions, Athena or Redshift, CloudWatch, and IAM, is required.
  • Familiarity with data orchestration tools such as Airflow or similar tools is required.

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 Amazon Web Services pipelines.
  • Build and manage data lakes and analytics-ready datasets using Amazon Web Services-native services.
  • Clean, standardize, and govern financial instrument identifiers, mappings, corporate actions, and historical data across vendors.
  • Design canonical financial data models covering 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 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.

Desired 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 such as Bloomberg, Refinitiv, Morningstar, or Nasdaq.
  • Knowledge of financial instruments, corporate actions, and identifiers such as ISIN, CUSIP, and RIC.
  • Experience building data catalogs, governance layers, or migrating legacy pipelines to cloud-native architectures.
  • Exposure to containerized environments such as Docker and Kubernetes and modern data warehouses such as Redshift, Snowflake, or BigQuery.

About the Company

MerQube

Index provider licensing cloud-based, rules-based indices

MerQube designs and calculates customized rules-based financial and insurance indices using cloud-native technology. Its offerings include thematic, ESG, factor, and retirement-focused indices, created and managed via a scalable platform that institutions license to design and deploy passive investment benchmarks. The product works by letting clients define rules and criteria for an index, with MerQube handling the calculation and maintenance of the index in real time or on a schedule, and licensing the resulting indices for use in investment products. Compared with competitors, MerQube emphasizes a specialized, scalable design-and-calculate platform tailored to financial and insurance needs, enabling highly customizable benchmarks rather than generic index options. Its goal is to support institutions in creating sophisticated, efficient, and trackable benchmarks for passive investing and related strategies, expanding the index-linked investment market.

Company size
51-200
Company stage
Series B
Total funding
$36M
Headquarters
New York City, New York
Founded
2019

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