Big Data Engineer

Responsibilities Design, build, and maintain ETL (Extract, Transform, Load) pipelines and database solutions to support real-time and batch analytics. Troubleshoot data processing workflows to ensure consistency, integrity, and reliable delivery of large-scale, complex data from multiple sources. Translate business requirements into technical specifications and well-structured, maintainable code, including complex programs, ad hoc queries, and analytical reports. Collaborate with business partners and technical teams to understand data needs and deliver high-quality, scalable data solutions. Lead all phases of solution development, providing technical guidance, mentoring junior engineers, and presenting technical considerations to stakeholders. Assess data quality, perform thorough code testing, and ensure accuracy and reliability of data products. Serve as a technical consultant to internal clients, providing data analysis support and best-practice recommendations. Contribute to data engineering standards, tooling, and best practices across the broader data organization. Test, validate, and implement new software releases through structured regression testing, partnering with vendors to resolve issues and ensure production readiness. Qualifications Minimum 8 years of experience in data analytics, programming, database administration, or data management. Bachelor's degree or equivalent combination of education and experience; master's degree preferred. Technical expertise in Python and AWS services, including S3, Redshift, Aurora, Athena, and Glue. Experience with version control and CI/CD tools such as GitHub, Bitbucket, and Bamboo. Familiarity with Agile methodologies, strong communication skills, and a growth-oriented mindset. Preferred experience with DPX blueprint processes, Dremio, Dell Boomi, or Attunity.

Created: 2026-03-10