Egen
Lead Data Engineer
Vaga remota de Data Engineering com fit claro de localização do candidato.
Publicada15 de jun. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Estados Unidos
Resumo da vaga
Lead Data Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
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
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