Director, Data Engineering – Google Cloud Platform
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Job Description
Director leading TTEC Digital’s Google Cloud data engineering practice. Building enterprise data platforms, GenAI infrastructure, and governance solutions for client transformations.
Responsibilities:
- Lead the Google Cloud data engineering function within the Data and Analytics team
- Define and execute the technical vision for the GCP Data Engineering functional practice
- Set standards for data modeling, ingestion pipelines, lakehouse architectures, and cloud cost optimization (FinOps)
- Oversee end-to-end design and deployment of enterprise data platforms using Google Cloud services
- Partner with Data Science and AI teams to build production-grade data pipelines, vector search infrastructure, and RAG frameworks using Vertex AI/Gemini Enterprise Agent Platform and BigQuery ML
- Lead GCP-native data governance, security, compliance, data lineage, access control, and metadata management
- Serve as the GCP Data SME during pre-sales activities, client workshops, and enterprise delivery engagements
- Translate complex business needs into modern GCP and Generative AI architectures
- Establish CI/CD, Terraform-based infrastructure as code, continuous data testing, and automated monitoring
- Manage, mentor, and scale an agile team of GCP Data Engineers
- Drive talent acquisition, skill development, Google Cloud certification pathways, and performance management
- Collaborate with client executives and lead solution delivery for scalable data foundations supporting analytics, AI/ML, and digital transformation
Requirements:
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field
- 10+ years of experience in data engineering and enterprise architecture
- 5+ years of direct people management experience leading agile engineering teams
- 4+ years of hands-on experience designing and building production data solutions natively on Google Cloud
- Deep experience with BigQuery, Dataflow, Pub/Sub, Cloud Composer/Airflow, Dataproc, and Cloud Storage
- Advanced proficiency in SQL and Python
- Practical experience deploying data pipelines for LLMs, vector search indexing, and GenAI workflows
- Experience 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 pipelines
- Knowledge of enterprise data security practices, including IAM, KMS, and Knowledge Catalog governance
- Exceptional presentation, consultative, and stakeholder management skills
- Ability to translate quantitative insights and AI capabilities into strategic business outcomes
- Google Cloud Professional Data Engineer certification is strongly preferred
Benefits:
- Annual incentive program
- Medical, dental, and vision benefits
- Tax-advantaged health care accounts
- Financial and income protection benefits
- Paid time off (PTO)
- Wellness time off
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