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
Skills Required
- 7+ years in data engineering
- At least 2 years in a lead or senior IC capacity on Google Cloud-based platforms
- Advanced BigQuery expertise (partitioning, clustering, slot management, storage optimization, query tuning)
- Hands-on experience building unified streaming and batch pipelines using Dataflow (Apache Beam), Dataproc, and Pub/Sub
- Production experience with Infrastructure as Code using Terraform
- Working knowledge of Apache Iceberg and open table formats for cross-engine interoperability
- Experience with data governance, automated data quality, metadata, and column-level lineage using Dataplex and Data Catalog
- Experience mentoring engineers and driving engineering standards
- 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
What We Do
Egen is a data engineering and cloud modernization firm partnering with leading Chicagoland companies to launch, scale, and modernize industry-changing technologies. We are catalysts for change who create digital breakthroughs at warp speed. Our team of cloud and data engineering experts are trusted by top clients in pursuit of the extraordinary. Our mission is to be an enabler of amazing possibilities for companies looking to use the power of cloud and data. We want to stand shoulder to shoulder with clients, as true technology partners, and make sure they succeed at what they have set out to do. We want to be disruptors, game-changers, and innovators who have played an important part in moving the world forward.








