Senior Data Engineer

Senior Data Engineer Salary: $123,833.00 – $170,184.00 Division & Section: Technology Services, Office of the Chief Technology Officer Job Type & Duration: Full-time, 1 Permanent Vacancy Shift Information: Monday to Friday,

Seeking a Senior Data Engineer to design, build, and operate data architecture for analytics, ML/AI, and BI on a large-scale consumer software platform. Responsibilities include ETL/ELT pipeline development, data quality frameworks, and collaborating with data scientists.

Seeking a Senior Data Engineer to design, build, and operationalize data pipelines and stores using technologies like Snowflake, AWS, and Apache Kafka. Responsibilities include data acquisition, ETL, quality checks, and ensuring security and scalability.

Seeking a Senior Data Engineer to design, build, and maintain scalable data platforms and pipelines using tools like Azure Fabric, Databricks, and Snowflake. Requires 4+ years experience and strong SQL/Python skills.

Seeking a Senior Data Engineer to design, build, and optimize data platform capabilities for analytics, reporting, and AI. Requires strong Python, SQL, and lakehouse experience.

About Terawatt Infrastructure The once in a century transition to autonomous and electric vehicles is underway and will require a multi‑trillion‑dollar investment in energy and charging infrastructure, and the real estate to site it on. Terawatt is the leader in delivering large scale, turnkey charging solutions for companies rapidly

Data Engineer responsible for developing data solutions, automating reporting pipelines, building real-time dashboards, and optimizing data queries using GCP technologies. Requires 5+ years of experience and strong SQL skills.

Seeking a Senior Data Engineer to design, develop, and implement data solutions using AWS technologies and Python. Responsibilities include building data pipelines, data modeling, and supporting the enterprise data platform.

Seeking a Senior Data Engineer to design and implement scalable data architectures, optimize data pipelines, and build/maintain data models and lakes. Role focuses on transforming raw data into ML-ready features and ensuring data quality and reliability.