Lead Data Engineer
Egen
About Egen:
Egen is a fast-growing and entrepreneurial company with a data-first mindset. We bring together the best engineering talent working with the most advanced technology platforms, including Google Cloud and Salesforce, to help clients drive action and impact through data and insights. We are committed to being a place where the best people choose to work so they can apply their engineering and technology expertise to envision what is next for how data and platforms can change the world for the better. We are dedicated to learning, thrive on solving tough problems, and continually innovate to achieve fast, effective results. If this describes you, we want you on our team.
Want to learn more about life at Egen? Check out these resources in addition to the job description.
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Role Overview:
We're looking for a Lead Data Engineer to architect and build modern, cloud-native data platforms on Google Cloud. You'll lead the design of unified batch and streaming pipelines, drive data quality and governance practices, and set the technical direction for open, interoperable data architectures. This is a hands-on leadership role for someone who enjoys solving complex data problems and mentoring engineers along the way.
What You'll Do:
- Architect and optimize large-scale data platforms on Google Cloud, with BigQuery as the analytical backbone
- Design and build unified batch and streaming pipelines that handle high-volume, mission-critical workloads
- Lead infrastructure-as-code practices, ensuring environments are repeatable, secure, and version-controlled
- Implement open table formats to enable cross-cloud and cross-engine data interoperability
- Establish automated data quality, metadata, and lineage practices across the data estate
- Partner with data scientists, analysts, and product teams to translate business needs into reliable data products
- Mentor engineers, review designs, and raise the bar on engineering standards
Must-Have Skills:
- 7+ years in data engineering, with at least 2 years in a lead or senior individual contributor capacity on Google Cloud-based platforms
- BigQuery (Advanced): Deep knowledge of BigQuery architecture, including partitioning, clustering, slot management, storage optimization, and query execution tuning
- Streaming & Batch Pipelines: Strong hands-on experience building unified pipelines using Dataflow (Apache Beam), Dataproc, and Pub/Sub
- Infrastructure as Code: Production experience developing and managing cloud infrastructure with Terraform
- Open Table Formats: Working knowledge of Apache Iceberg, including its role in enabling cloud and engine interoperability (e.g., across BigQuery, Spark, Snowflake)
- Data Governance: Experience with Dataplex and Data Catalog for automated data quality checks, metadata tagging, and column-level lineage from source to destination
Nice-to-Have Skills:
- Experience leading or mentoring data engineering teams
- Familiarity with CI/CD for data pipelines (Cloud Build, GitHub Actions)
- Exposure to multi-cloud or hybrid data architectures
- Background in regulated industries (healthcare, financial services) where governance and lineage are critical