Google Cloud Platform Data Platform Lead

Data Platform Lead Analytics Engineering (Google Cloud Platform/BigQuery/DBT/Prefect)

Location: Remote (with occasional on-site visits to client headquarters in Carlsbad, CA)

Duration:- 6-12 Months+

About the Role

• One of my clients is seeking a seasoned Data Platform Lead to oversee and evolve our global data infrastructure within Google Cloud Platform.
• As the contractor responsible for this role, you will architect, implement, and manage scalable data pipelines using BigQuery, DBT, and workflow orchestration tools such as Prefect or Composer.
• You will partner closely with commercial and operations stakeholders to transform raw data into actionable insights driving our commercial opportunity analyses and operational reporting.
• In addition to hands-on technical leadership, you will mentor and guide a team of analytics engineers, ensuring best practices in data modelling, transformation, and orchestration across the organization.

Key Responsibilities

You will own the end-to-end data platform life cycle, from design through production support. This includes:

• Data Platform Strategy & Architecture: Lead the definition and evolution of client s Google Cloud Platform data architecture designing BigQuery schemas optimized for high-volume satellite telemetry, customer usage, and financial data. Partner with cloud infrastructure teams to ensure security, cost optimization, and performance SLAs are met.
• DBT Development & Best Practices: Establish and enforce a robust DBT framework for version-controlled, tested data transformations. Collaborate with analysts and engineers to translate complex business requirements into reusable DBT models that support commercial forecasting (e.g., churn, ARPU, new market opportunities) and real-time operational dashboards.
• Orchestration & Workflow Management: Design, implement, and maintain reliable, scalable workflows using Prefect or Composer. Ensure data pipelines are fault-tolerant and self-healing streamlining batch and near-real-time patterns for ingesting satellite telemetry, network performance metrics, and billing feeds.
• Team Leadership & Mentorship: Supervise a distributed team of analytics engineers assessing skill gaps, assigning sprint tasks, and driving continuous improvement. Establish coding standards, conduct regular code reviews, and facilitate knowledge-share sessions around Google Cloud Platform best practices, SQL optimization, and data quality frameworks.
• Stakeholder Collaboration: Act as a consultative partner to commercial analytics, finance, and operations leaders. Translate high-level KPIs into technical specifications, ensuring data products (e.g., opportunity pipelines, regional revenue heatmaps, fleet utilization reports) exceed stakeholder expectations for accuracy, latency, and usability.
• Operational Excellence & Monitoring: Build and maintain monitoring dashboards (e.g., Stackdriver, Looker) to proactively identify pipeline failures, data anomalies, or cost overruns. Develop runbooks and incident-response procedures to restore service rapidly when issues occur.
• Continuous Improvement: Stay current on emerging Google Cloud Platform services evaluating new serverless options (e.g., BigQuery BI Engine, Dataflow Flex Templates) or orchestration tools (e.g., Airflow, Vertex AI pipelines) that could enhance our data strategy. Propose iterative enhancements to our data stack and rollout roadmaps accordingly.

Required Qualifications

• 10+ years of professional experience designing, building, and managing cloud-native data platforms specifically within Google Cloud Platform.
• Proven expertise with BigQuery at scale: partitioning, clustering, pricing models, and performance tuning for petabyte-scale tables.
• Hands-on experience authoring modular, test-driven DBT projects (models, macros, seeds, snapshots) in a collaborative Git workflow.
• Deep familiarity with orchestrators such as Prefect or Composer (Airflow): designing DAGs, handling retries, SLA misses, and integrating custom operator logic.
• Demonstrated track record leading a team of analytics engineers (5+ members), including conducting code reviews, providing mentorship, and enforcing data engineering best practices.
• Strong SQL fluency: able to construct complex window functions, advanced aggregations, CTEs, and UDFs.
• Familiarity with data ingestion patterns: streaming data (Pub/Sub to BigQuery), batch ETL (Cloud Storage BigQuery), and change data capture (CDC) mechanisms.
• Clear, concise communication skills capable of translating technical concepts for non-technical stakeholders and documenting architecture decisions in an actionable manner.
• Bachelor s degree in Computer Science, Engineering, Data Science, or related field (or equivalent professional experience).

Preferred Qualifications

• Prior experience within the telecommunications or satellite industries, particularly dealing with high-volume telemetry, network performance, or billing data.
• Familiarity with additional Google Cloud Platform services such as Dataflow, Pub/Sub, Firestore, and Looker for visualization/BI.
• Hands-on Python proficiency (3+ years) in data engineering contexts writing custom transformations, UDFs for BigQuery, or Prefect tasks.
• Experience implementing data governance frameworks: lineage tracking (e.g., Data Catalog), core metadata management, and data quality (e.g., Great Expectations).
• Knowledge of containerization (Docker) and infrastructure as code (Terraform, Deployment Manager) for reproducible environments and IaC-driven deployments.
• Prior involvement in MLOps or embedding simple machine learning models within data pipelines (e.g., BigQuery ML, Vertex AI).