Lead design and delivery of scalable data platforms on Google Cloud Platform (Google Cloud Platform).
Own end-to-end data architecture using BigQuery, Cloud Storage, Dataflow, and Pub/Sub.
Build and optimize batch and streaming pipelines for high-volume, high-velocity data.
Define data modeling, partitioning, and performance optimization best practices.
Lead a team of data engineers; provide technical guidance, reviews, and mentorship.
Collaborate with product, analytics, and ML teams to translate business needs into data solutions.
Implement data quality, validation, monitoring, and observability frameworks.
Ensure security, governance, and compliance using IAM, DLP, and encryption standards.
Drive CI/CD, automation, and infrastructure-as-code using Terraform and Cloud Build.
Optimize cost and performance across Google Cloud Platform services and data workloads.
Establish standards for coding, testing, documentation, and release management.
Troubleshoot complex data issues and lead root-cause analysis efforts.
Evaluate and introduce new Google Cloud Platform services and modern data engineering tools.
Partner with stakeholders to define roadmaps, SLAs, and data platform strategy.
Required: 8+ years in data engineering, strong Google Cloud Platform expertise, leadership experience preferred.
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Remote or Dallas, Texas
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Today
ITS W2 Position. Position : Google Cloud Platform Data Engineer Location : Need to Travel to client place in Hartford, CT or Dallas, TX Once in a Month 10+ years of experience in Data Engineering, with at least 3 years in Google Cloud Platform. Strong hands-on experience in Python, Pyspark, and complex SQL. Solid knowledge of Google Cloud Platform services: BigQuery, Dataflow, Cloud Storage, Pub/Sub, Composer, and Dataproc. Familiarity with CI/CD, Git, and DevOps practices in cloud data en
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