[Remote] Director, Data Engineering (Google Cloud Platform)
Note: The job is a remote job and is open to candidates in USA. TTEC Digital is a customer experience and digital transformation company that helps clients support their employees and improve customer experiences. The Director, Data Engineering (GCP) will lead the Google Cloud data engineering practice, overseeing modern data architecture, data platforms, real-time analytics, Generative AI infrastructure, governance, and security. The role also involves client engagement, solution delivery, and managing and developing GCP data engineering teams.
Responsibilities
- Define and execute the technical vision for our GCP Data Engineering functional practice, setting standards for data modeling, ingestion pipelines, lakehouse architectures, and cloud cost optimization (FinOps)
- Oversee the end-to-end design and deployment of enterprise data platforms using core Google Cloud services, including BigQuery, Dataflow, Dataproc, Pub/Sub, Dataplex (Knowledge Catalog), and Cloud Storage
- Partner directly with the Data Science and AI functional practice within the team to design and build production-grade data pipelines, vector search infrastructure, and retrieval-augmented generation (RAG) frameworks powered by the Gemini Enterprise Agent Platform (i.e., Vertex AI) and BigQuery ML
- Lead the implementation of GCP-native data governance, security, and compliance frameworks—establishing data lineage, row/column-level access control, and metadata management via Knowledge Catalog and IAM
- Serve as the GCP Data SME during pre-sales activities, client workshops, and enterprise delivery engagements—translating complex business needs into modern GCP and Generative AI architectures
- Establish CI/CD, IaC (Terraform), continuous data testing, and automated monitoring (Dataflow/BigQuery logs) to ensure maximum reliability, security, and accuracy across client data assets
- Manage, mentor, and scale an agile team of GCP Data Engineers. Drive talent acquisition, skill development, Google Cloud certification pathways, and performance management aligned with practice growth
Skills
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field
- 10+ years in data engineering and enterprise architecture, with 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 (BigQuery, Dataflow, Pub/Sub, Cloud Composer/Airflow, Dataproc, Cloud Storage)
- Advanced proficiency in SQL and Python
- Practical experience deploying data pipelines for LLMs, vector search indexing, and GenAI workflows alongside frameworks like Apache Beam, PySpark, and NoSQL databases
- Proven track record in modern data modeling, ELT/ETL pipeline architecture, real-time streaming processing, and building Medallion/Lakehouse architectures on cloud
- Strong understanding of Terraform for GCP infrastructure, CI/CD pipelines, and enterprise data security practices (IAM, KMS, Knowledge Catalog governance)
- Exceptional presentation, consultative, and stakeholder management skills—with a demonstrated ability to translate quantitative insights and AI capabilities into strategic business outcomes
- Google Cloud Professional Data Engineer certification is strongly preferred
Benefits
- Medical, dental, vision
- Tax-advantaged health care accounts
- Financial and income protection benefits
- Paid time off (PTO) and wellness time off
- Remote work arrangement
Company Overview
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