Lead Data Engineer

Ovii's Interpretation of the Role

Lead the architecture and implementation of cloud‑native data platforms on Google Cloud, driving batch and streaming pipelines, data quality, and governance. Mentor engineers while setting technical direction for interoperable data solutions.

Role Snapshot

• Lead Data Engineer
• Remote, Full‑Time
• 7+ years data engineering experience
• Hands‑on technical leadership
• Mentor and raise engineering standards

Must-Have Requirements

• Google Cloud Platform
• BigQuery (advanced)
• Data pipelines (Dataflow, Dataproc, Pub/Sub)
• Terraform
• Apache Iceberg
• Dataplex
• Data Catalog
• Data engineering
• Google Cloud platforms

Nice-to-Have Signals

• Team leadership / mentoring
• CI/CD for data pipelines (Cloud Build, GitHub Actions)
• Multi‑cloud data architectures
• Experience in regulated industries (healthcare, financial services)
• Team leadership
• CI/CD for data pipelines
• Regulated industry experience

Work Setup

• Work mode: REMOTE
• Remote scope: UNSPECIFIED
• Employment type: Full-Time

Eligibility Gates

• Background check: standard hiring verification practices

Not Specified in JD

• Visa sponsorship
• Education requirement
• Certifications
• Relocation
• Travel
• Security clearance
• Coding test

What You'll Likely Work On

• Architect and optimize large‑scale data platforms on Google Cloud with BigQuery as the analytical core
• Design and build unified batch and streaming pipelines using Dataflow, Dataproc, and Pub/Sub
• Implement infrastructure‑as‑code with Terraform to ensure repeatable, secure environments
• Adopt open table formats like Apache Iceberg for cross‑cloud data interoperability
• Establish automated data quality, metadata, and lineage using Dataplex and Data Catalog
• Partner with data scientists, analysts, and product teams to deliver reliable data products
• Mentor engineers, review designs, and elevate engineering standards

Good Fit If You Have

• Enjoys solving complex data problems
• Has experience leading or mentoring data engineering teams
• Familiar with CI/CD pipelines for data workloads