About the role

  • Data Engineering Lead managing enterprise-scale data platforms using AWS, Snowflake, and Databricks in financial services. Leading data engineering teams and ensuring data governance.

Responsibilities

  • Lead the design and implementation of enterprise data platforms (Data Lakes, Lakehouse, DWH)
  • Architect scalable, secure, and high-performance data architectures on AWS
  • Build modern ETL/ELT pipelines using PySpark, SQL, Spark
  • Implement AWS services (S3, Glue, EMR, Lambda, Redshift)
  • Lead and mentor data engineering teams
  • Define best practices, reusable frameworks, and coding standards
  • Enable enterprise analytics through curated data models
  • Ensure data governance, quality, and lineage
  • Optimize pipelines for performance and cost
  • Work closely with financial domain stakeholders

Requirements

  • 10–15 years of experience in Data Engineering / Analytics
  • Strong AWS, Snowflake, Databricks experience
  • Experience building enterprise data lakes and lakehouses
  • Experience in Financial Services / Banking / Capital Markets
  • AWS Certified Solutions Architect / Data Analytics (Preferred)
  • Databricks Certified Data Engineer (Preferred)
  • Snowflake SnowPro Certification (Preferred)

Benefits

  • Health insurance
  • Professional development
  • Flexible work arrangements
  • Paid time off

Job title

Data Engineering Lead

Job type

Experience level

Senior

Salary

Not specified

Degree requirement

Bachelor's Degree

Location requirements

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