Temporary Databricks Data Engineer Jobs in Denton, TX

Allata is a global consulting and technology services firm founded in 2016, with 350+ employees across the US, India, and Argentina. We partner with some of the world\'s largest enterprises to move AI from idea to production — building intelligent agents, data foundations, and governance frameworks that scale.

Our teams work at the intersection of strategy, engineering, data, and design, helping clients modernize their technology, unlock data value, and create meaningful digital experiences. At Allata, you\'ll join an agile, cross-functional team that works closely alongside clients — making a real impact and building lasting partnerships. 

We are seeking a skilled Data Engineer to join our team and contribute to data-driven initiatives within the healthcare industry. This role focuses on designing, building, and optimizing scalable data solutions that support analytics, reporting, and advanced data use cases in regulated environments.

• Design, develop, and maintain scalable data pipelines using Databricks (PySpark) and Python.
• Build and optimize ETL/ELT processes within Azure cloud environments.
• Implement data models following modern Data Lakehouse principles (e.g., Medallion architecture).
• Ensure data quality, consistency, and performance across ingestion, staging, and curated layers.
• Collaborate with data architects, analysts, and business stakeholders to translate healthcare data requirements into technical solutions.
• Develop reusable data transformation logic and modular processing components.
• Support deployment processes following CI/CD and DevOps best practices.
• Monitor and optimize data workflows for performance, scalability, and reliability.
• Contribute to data governance, security, and compliance practices relevant to healthcare environments.

• Strong hands-on experience with Databricks in Azure environments (PySpark, notebooks, clusters, Delta Lake).
• Advanced proficiency in Python and PySpark for distributed data processing.
• Experience building and optimizing data pipelines in Azure (Azure Data Factory, Azure SQL, Data Lake Storage, or similar).
• Solid understanding of data warehousing and Data Lakehouse concepts, including Medallion architecture.
• Strong SQL skills, including stored procedures and performance optimization.
• Experience with relational database systems such as SQL Server, PostgreSQL, Oracle, Azure SQL, or similar.
• Experience with batch and streaming data processing patterns and techniques.
• Familiarity with CI/CD and DevOps practices for data pipeline deployment.

• Experience with modern data integration tools such as Fivetran, Microsoft Fabric, or similar.
• Experience with custom Databricks deployments (e.g., custom .whl packages, in-session notebook scripts, parallel execution across worker nodes).
• Experience with file compaction strategies in distributed environments.
• Knowledge of data governance, security, and compliance practices in regulated industries such as healthcare.
• Experience working with large, complex datasets in cloud-based distributed environments

• Strong analytical and problem-solving skills.
• Ability to work effectively in cross-functional and distributed teams.
• Clear communication skills, with the ability to explain technical concepts to non-technical stakeholders.
• Proactive mindset with a strong sense of ownership.
• Commitment to delivering high-quality, reliable data solutions

At Allata, we value differences.

Allata is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Allata makes employment decisions without regard to race, color, creed, religion, age, ancestry, national origin, veteran status, sex, sexual orientation, gender, gender identity, gender expression, marital status, disability or any other legally protected category.

This policy applies to all terms and conditions of employment, including but not limited to, recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.