Director, Data Engineering - GCP

Job description

At TTEC Digital, we coach clients to ensure their employees feel valued, and fully supported, because an amazing customer experience is an employee first process. Our vision is the same, a place where employees know they can thrive. At TTEC Digital, we coach clients to ensure their employees feel valued and fully supported, because an amazing customer experience is an employee-first process. Our vision is the same: a place where employees know they can thrive. As the Director, Data Engineering (GCP), you will lead our Google Cloud data engineering function within the Data and Analytics team. You will play a pivotal, highly visible leadership role driving modern data architecture, advanced ingestion, real-time analytics, Generative AI infrastructure, and enterprise data governance—all natively powered by Google Cloud Platform. We are looking for a hands-on, strategic technology leader who combines deep GCP technical expertise with a passion for mentoring high-performing engineering teams. You will collaborate closely with client executives, lead solution delivery, and build scalable, business-critical data foundations that power advanced analytics, AI/ML and enterprise digital transformations. ### What you'll be doing: - **Functional Leadership:** 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). - **GCP Solution Delivery:** 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. - **GenAI & ML Enablement:** 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. - **Data Governance & Security:** 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. - **Client & Executive Partnership:** 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. - **Quality & Engineering Excellence:** 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. - **Team Development & Strategy:** 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 and experience you will bring: - **Education:** Bachelor's degree in Computer Science, Engineering, Mathematics, or a related quantitative field. - **Core Experience:** 10+ years in data engineering and enterprise architecture, with 5+ years of direct people management experience leading agile engineering teams. - **Deep GCP Mastery:** 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). - **Generative AI & Modern Stack Skills:** 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. - **Architectural Expertise:** Proven track record in modern data modeling, ELT/ETL pipeline architecture, real-time streaming processing, and building Medallion/Lakehouse architectures on cloud. - **DevOps & Governance:** Strong understanding of Terraform for GCP infrastructure, CI/CD pipelines, and enterprise data security practices (IAM, KMS, Knowledge Catalog governance). - **Client Engagement & Business Acumen:** Exceptional presentation, consultative, and stakeholder management skills—with a demonstrated ability to translate quantitative insights and AI capabilities into strategic business outcomes. - **Certifications:** Google Cloud Professional Data Engineer certification is strongly preferred.