Senior Data Engineer - AI-Ready Databricks Lakehouse

Hill Air Corporation; Dallas (TX); Presencial; USD 140 000 - 170 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Medical Insurance

Vision Insurance

401(k) with company match

Vacation time

Paid family caregiver leave

Resumo da oferta

Hillwood, a Perot Company, seeks a Senior Data Engineer in Dallas to advance the enterprise Data Lakehouse on Databricks. You will design scalable pipelines, models, and governance to deliver AI-ready data across business units. Collaboration with stakeholders will ensure trusted analytics and platform reliability.

The role emphasizes secure, cost-efficient data processing, CI/CD practices, and strong technical leadership to enable data-driven decision making across the organization.

Qualificações

• Bachelor's degree in Computer Science or a related field.
• Minimum five years of data engineering experience with production Databricks deployments.
• Experience administering Unity Catalog and data governance.

Responsabilidades

• Design, develop, and maintain scalable data pipelines in Databricks.
• Develop data models across Bronze, Silver, and Gold layers.
• Implement CDC and incremental processing for fresh data.
• Ensure data quality and governance across the data lakehouse.

Conhecimentos

SQL

Python

PySpark

Databricks lakehouse

Data modeling

Data governance

CI/CD

Data quality

Stakeholder communication

Cloud data platforms

Formação académica

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related field

Ferramentas

Databricks

Unity Catalog

Azure DevOps

GitHub

Descrição da oferta de emprego

Hillwood, a Perot Company, seeks a Senior Data Engineer in Dallas to advance the enterprise Data Lakehouse on Databricks. You will design scalable pipelines, models, and governance to deliver AI-ready data across business units. Collaboration with stakeholders will ensure trusted analytics and platform reliability.

The role emphasizes secure, cost-efficient data processing, CI/CD practices, and strong technical leadership to enable data-driven decision making across the organization.