Director, Data Engineering – Google Cloud Platform

This is a fully remote position, open to applicants in Texas.

📋 Description

• Lead the data engineering initiatives for Google Cloud within the Data and Analytics team.

• Define and implement the technical vision for the GCP Data Engineering functional area.

• Set benchmarks for data modeling, ingestion pipelines, lakehouse frameworks, and cloud cost management (FinOps).

• Oversee the comprehensive design and deployment of enterprise data platforms utilizing Google Cloud services.

• Collaborate with Data Science and AI teams to develop production-quality data pipelines, vector search infrastructure, and RAG frameworks leveraging Vertex AI/Gemini Enterprise Agent Platform and BigQuery ML.

• Lead GCP-native data governance, including security, compliance, data lineage, access control, and metadata management.

• Act as the GCP Subject Matter Expert during pre-sales efforts, client workshops, and enterprise delivery engagements.

• Convert intricate business requirements into contemporary GCP and Generative AI architectures.

• Establish CI/CD processes, Terraform-based infrastructure as code, continuous data testing, and automated monitoring systems.

• Manage, mentor, and expand a nimble team of GCP Data Engineers.

• Drive talent acquisition, skill enhancement, Google Cloud certification paths, and performance management initiatives.

• Collaborate with client executives to spearhead solution delivery for scalable data foundations that support analytics, AI/ML, and digital transformation.

⛳️ Requirements

• Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative discipline.

• Over 10 years of experience in data engineering and enterprise architecture.

• More than 5 years of direct management experience leading agile engineering teams.

• At least 4 years of hands-on experience in designing and developing production data solutions on Google Cloud.

• Extensive experience with BigQuery, Dataflow, Pub/Sub, Cloud Composer/Airflow, Dataproc, and Cloud Storage.

• Advanced skills in SQL and Python programming.

• Practical experience in deploying data pipelines for LLMs, vector search indexing, and GenAI workflows.

• Familiarity with Apache Beam, PySpark, and NoSQL databases.

• Expertise in modern data modeling, ELT/ETL pipeline architecture, real-time streaming processing, and Medallion/Lakehouse architectures.

• Strong understanding of Terraform for GCP infrastructure and CI/CD processes.

• Knowledge of enterprise data security practices, including IAM, KMS, and Knowledge Catalog governance.

• Outstanding presentation, consultative, and stakeholder management abilities.

• Capacity to translate quantitative insights and AI capabilities into strategic business results.

• Google Cloud Professional Data Engineer certification is highly preferred.

🏝️ Benefits

• Annual incentive program.

• Comprehensive medical, dental, and vision coverage.

• Tax-advantaged healthcare accounts.

• Financial and income protection benefits.

• Paid time off (PTO).

• Wellness time off.