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# Data Engineer

- **Company:** Robert Half
- **Location:** Dallas, TX, United States
- **Contract:** Permanent contract
- **Skills:** Query Performance, Computer Programming, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Python (Programming Language), Performance Tuning, DataOps, SQL Databases, System Availability, Data Layers, Pyspark, Data Delivery, Data Pipelines, Databricks
- **Published:** September 12, 2026
- **Apply:** https://dejobs.org/x/x/36B2F908A81E4E8CB4B4C7803C65ADC9/job/

## About the Role

* Work with business and technical partners to translate data needs into practical engineering solutions that support trusted insights. Requirements * Hands-on experience with Databricks in a data engineering environment.

 * Strong programming skills in Python, including building data workflows with PySpark.

 * Solid understanding of ETL development and data pipeline design.

 * Proficiency in SQL for data transformation, analysis, and performance tuning.

 * Experience working with medallion architecture and managing Bronze, Silver, and Gold data layers.

 * Knowledge of data engineering best practices related to testing, monitoring, documentation, and long-term supportability.

 * Effective communication skills with the ability to work across technical teams and business stakeholders.

 * Strong business awareness and the ability to align engineering work with reporting and analytics objectives. Technology Doesn't Change the World, People Do.®

## Description

Description We are looking for a Data Engineer to join a growing team and contribute to the delivery of reliable, analytics-ready data solutions. This contract opportunity with potential for a permanent role is ideal for someone who enjoys building scalable data pipelines, improving data models, and partnering with technical and business stakeholders to support reporting, self-service analytics, and data science. The role offers the chance to work hands-on with Databricks, Python, PySpark, SQL, and modern data engineering practices in a collaborative environment focused on quality and performance.

Responsibilities:

 * Build, maintain, and enhance data pipelines that support dependable data availability for analytics and reporting needs.

 * Collaborate with data engineering leaders to troubleshoot defects, resolve pipeline issues, and improve overall platform stability.

 * Develop transformation logic using Python, PySpark, SQL, and Databricks to prepare clean, usable datasets for downstream consumers.

 * Design and refine data models that improve usability, consistency, and performance across reporting and analytical workloads.

 * Apply layered data architecture principles, including Bronze, Silver, and Gold structures, to organize and manage data effectively.

 * Establish and follow engineering standards for validation, testing, monitoring, and documentation to strengthen data quality and maintainability.

 * Optimize processing and query performance to support efficient data delivery at scale.