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# Lead Google Cloud Platform Data Engineer/Looker

- **Company:** HMG America
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Training Data, Query Performance, Adaptable Database Systems, Airflow, Data Analysis, BigQuery, Cloud Storage, Cluster Analysis, Software Quality, Computer Programming, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Vault Modeling, Data Warehousing, DevOps, Data Flow Control, Github, Identity and Access Management, Python (Programming Language), Machine Learning, Query Optimization, Cloudera, SQL Databases, Data Streaming, Google Cloud, Sql Optimization, Gitlab-ci, Data Lineage, Data Analytics, Star Schema, Google Bigquery, Terraform, Looker Analytics, Data Pipelines, Apache Beam, Jenkins
- **Published:** October 18, 2026
- **Apply:** https://www.dice.com/job-detail/27a96784-54ab-47b4-960d-5fd0ee67cab4

## About the Role

* Experience: 8+ years of total data engineering experience, with 4+ years of hands-on expertise leading Google Cloud Platform data implementations at enterprise scale.
 * Core Google Cloud Platform Stack: Advanced proficiency in BigQuery, Cloud Composer, Dataflow, Pub/Sub, Cloud Storage, and Dataproc.
 * Programming & SQL: Expert-level mastery of Python and Advanced SQL (window functions, query tuning, partitioning, clustering).
 * Data Transformation & CI/CD: Hands-on experience with dbt, Terraform (IaC), and modern CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins).
 * Leadership: Proven track record of leading technical projects, mentoring engineers, and setting data architecture strategy.

## Description

We are seeking an experienced Lead Google Cloud Platform Data Engineer to design, architect, and scale our enterprise data infrastructure on Google Cloud Platform (Google Cloud Platform). In this role, you will lead the technical vision for our data environment, drive end-to-end ELT/ETL pipeline architecture, and mentor a team of engineers. You will collaborate closely with data architects, software engineers, data scientists, and business stakeholders to turn complex data into actionable business intelligence and AI-ready data products., Technical Leadership & Architecture

 * Data Architecture: Design, build, and optimize scalable, reliable, and cost-efficient data pipelines and data warehouse structures on Google Cloud Platform.
 * Team Governance & Standards: Define standards and best practices for code quality, data modeling, CI/CD, testing, monitoring, and security across the data engineering workflow.
 * Mentorship: Provide technical direction, lead design reviews, and mentor mid-level and senior data engineers.

Data Engineering & Analytics Infrastructure

 * Pipeline Development: Build robust batch and real-time streaming data ingestion pipelines using Google BigQuery, Dataflow (Apache Beam), Pub/Sub, and Dataproc.
 * Orchestration: Implement automated workflow orchestration using Cloud Composer (Apache Airflow) or dbt.
 * Data Modeling: Create scalable data models (Kimball, Star/Snowflake schemas, Data Vault) optimized for analytical query performance and cost governance in BigQuery.
 * Quality & Monitoring: Implement automated data quality checks, data lineage tracking, alert frameworks, and proactive system health monitoring.

Collaboration & Security

 * Cross-Functional Strategy: Partner with Analytics, Data Science, and DevOps teams to deliver self-service data solutions and support advanced analytics/ML models.
 * Security & Compliance: Ensure adherence to data governance policies, IAM best practices, encryption at rest/in transit, and compliance frameworks (GDPR, HIPAA, SOC 2).