Lead Data Engineer

4 дн. назад

140k–190k USD / yearLeadRemote

google clouddata pipelinesstreamingbatch processingdata governance

Lead Data Engineer to architect and build modern, cloud-native data platforms on Google Cloud, driving data quality and mentorship.

About :    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 ? Check out these resources in addition to the job des

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

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

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