Lead Google Cloud Platform Data Engineer

Hybrid (Madison, WI)
Long-Term Contract

About the Role

We are seeking an experienced Lead Data Engineer to join a high-impact data and analytics team supporting initiatives across AI, Sales, Marketing, and Customer Analytics. This is a hands-on technical leadership role where you will design, build, and optimize scalable cloud-based data solutions while mentoring fellow engineers and driving engineering best practices.

This position is approximately 70-75% hands-on development and 25-30% technical leadership/mentoring.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines and ETL workflows.
• Build and optimize data warehouse solutions and cloud-based data platforms.
• Lead technical design discussions and promote best practices across engineering teams.
• Mentor junior and mid-level engineers on architecture, coding standards, and performance optimization.
• Ensure data quality, security, privacy, governance, and integrity throughout the data lifecycle.
• Collaborate with business stakeholders to translate requirements into data solutions.
• Develop reusable frameworks, libraries, and automation capabilities.
• Support distributed data processing and large-scale analytics workloads.
• Create and maintain documentation for critical processes and operational support.

Required Qualifications

• 8+ years of experience in Data Engineering, Data Warehousing, or Big Data Engineering.
• Expert-level experience with Google Cloud Platform (Google Cloud Platform).
• Strong hands-on expertise in Python development for data processing and ETL frameworks.
• Advanced SQL skills with extensive experience in relational and analytical databases.
• Experience building scalable data pipelines and cloud-native data solutions.
• Strong knowledge of Spark, Hadoop, or other distributed data processing technologies.
• Experience with data modeling, dimensional modeling, and star schema design.
• Understanding of database internals, indexing, transactions, and query optimization.
• Experience with REST APIs and web services.
• Strong communication skills and ability to work directly with business stakeholders.

Preferred Qualifications

• Experience with Machine Learning Engineering or ML-enabled data platforms.
• Exposure to tools such as scikit-learn, Spark ML, H2O, or similar ML frameworks.
• Experience with Infrastructure as Code (Terraform, Docker, CloudFormation, etc.).
• Experience with CI/CD and DevOps tools including Jenkins and Git.
• Background within insurance, financial services, or other data-driven industries.

Ideal Candidate

• Strong Google Cloud Platform, Python, and SQL expertise.
• Proven experience designing enterprise-scale data platforms.
• Comfortable mentoring engineers and influencing technical direction.
• Able to bridge business requirements with technical solutions.
• Passionate about modern data engineering, analytics, and cloud technologies.

Recommended Dice Filters

• Must Have Skills: Google Cloud Platform, Python, SQL
• Nice to Have: Spark, BigQuery, Terraform, Machine Learning
• Experience Level: 8+ Years
• Employment Type: Contract
• Location: Wisconsin (Hybrid)