Big Data Engineering Lead

Summary

The Big Data Engineering Lead will oversee the development and maintenance of enterprise data pipelines, data models, and services while leading a high-performing engineering team. The role requires expertise in Python, PySpark, SQL, and modern data architecture patterns to ensure scalable and reliable data solutions.

Responsibilities

  • Lead the technical leadership, engineering delivery, and quality of the Data Foundation platform
  • Build and maintain enterprise data pipelines, data products, canonical data models, and data services
  • Partner with Service Owner, Architecture Team, and Platform Engineering Lead to deliver scalable, trusted, and maintainable data solutions
  • Accountable for engineering execution, solution quality, and operational reliability
  • Develop a high-performing data engineering team

Requirements

  • 8+ years of experience in data engineering, software engineering, or enterprise data platform development
  • 3+ years of technical leadership experience leading engineering teams or large-scale data initiatives
  • Advanced SQL and data modeling expertise
  • Strong Python and PySpark development experience
  • Deep understanding of ETL and ELT architecture patterns
  • Experience implementing Master Data Management solutions
  • Experience building RESTful APIs and data services
  • Familiarity with GraphQL and modern integration approaches
  • Understanding of microservices-based architectures
  • Experience implementing event-driven and real-time data processing solutions
  • Strong understanding of data quality frameworks, metadata management, and data lineage concepts

See also

Data Engineering jobs by country — openings, pay and top skills →

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