Database Administrator

Position Summary

The Sr. Data Engineer / Database Administrator supports and evolves the Enterprise Data Warehouse ecosystem running Teradata on Google Cloud Platform (GCP) into a modern Lakehouse supporting data products. This role blends traditional database administration with modern data engineering and AI/ML enablement responsibilities.

The individual will contribute to physical database design, platform reliability, performance optimization, data pipeline engineering, automation, and cloud cost optimization. The role also supports advanced analytics, AI/ML workloads, and scalable data architecture to enable enterprise-wide data-driven decision-making.

A bachelors degree in computer science, Information Systems, Data Engineering, Engineering, or a related technical field is preferred. The position is ideal for someone familiar with, and interested in building expertise across, database administration, cloud infrastructure, data engineering, and AI/ML platform integration.

The culture of our organization places a strong emphasis on teamwork, so social and interpersonal skills are equally important as technical capability.

Major Responsibilities:

Database & Platform Administration

• Support Teradata database operations including monitoring, performance tuning, backup/recovery, object deployment, and user provisioning

• Assist in implementing automation for routine DBA operational tasks using scripting (Shell/Python).

• Support Teradata NOS, QueryGrid, and cross-platform data movement capabilities.

• Participate in planned maintenance and rotational on-call support.

• Participate in doing POCs to evaluate features and functionalities.

Cloud & Infrastructure (GCP-Focused)

• Support Teradata deployments on GCP, including integration with GCS, BigQuery, and other cloud-native services.

• Monitor and optimize cloud resource utilization to support FinOps initiatives and cost efficiency goals.

• Contribute to infrastructure-as-code and CI/CD implementations for database object deployments and platform changes.

Data Engineering

• Collaborate with data architecture and integration teams to ensure adherence to enterprise data standards.

• Contribute to data quality, metadata management, and lineage initiatives.

Collaboration & Communication

• Work closely with architecture, integration, reporting, analytics, and data science teams.

• Communicate project status, risks, and technical findings clearly to stakeholders.

• Performs other duties as assigned

• Practices and adheres to the Code of Conduct philosophy and Mission and Value Statement.”