Senior Databricks Engineer
<p>We are looking for an experienced Senior Databricks Engineer to support enterprise data initiatives. This Long-term Contract position will focus on building and enhancing scalable data solutions, including extracting data from ServiceNow and structuring it for downstream ARDoc consumption within a broader enterprise architecture program. The role will partner with engineering, analytics, and platform teams to deliver reliable, governed, and high-performing data pipelines on Databricks.</p><p><br></p><p>Responsibilities:</p><p>• Develop and maintain robust data pipelines in Databricks using Apache Spark to support enterprise reporting and analytical use cases.</p><p>• Extract and transform data from ServiceNow, then create and manage structured tables that supply ARDoc as part of a larger architecture initiative.</p><p>• Design layered data models using Delta Lake practices to improve scalability, data usability, and long-term maintainability.</p><p>• Configure and manage Databricks jobs, workflows, and compute resources to improve processing efficiency and platform stability.</p><p>• Investigate performance issues across Spark workloads and implement tuning strategies that improve speed, reliability, and cost control.</p><p>• Establish data governance practices through cataloging, lineage visibility, and secure access controls within the Databricks environment.</p><p>• Work closely with data scientists, analysts, and platform teams to deploy production-ready data assets and support advanced analytics needs.</p><p>• Provide technical guidance to other engineers by promoting engineering standards, reviewing designs, and sharing platform best practices.</p>
• At least 5 years of experience in data engineering working with large-scale or distributed data processing platforms.<br>• Minimum 3 years of hands-on experience building solutions in Databricks within production environments.<br>• Strong coding ability in Python, especially PySpark, with additional SQL proficiency for data transformation and analysis.<br>• Solid knowledge of Apache Spark concepts, including execution behavior, performance tuning, and resource management.<br>• Practical experience with Delta Lake features such as schema evolution, versioned data management, and reliable transactional processing.<br>• Familiarity with cloud-based data ecosystems and orchestration tools used to schedule, monitor, and manage data workloads.<br>• Experience using version control and CI/CD practices to support repeatable and controlled data engineering deployments.<br>• ServiceNow knowledge is highly valued, especially for roles involving data extraction and integration into downstream platforms.
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- Cincinnati, OH
- remote
- Temporary / Contract
-
76.95 - 89.1 USD / Hourly
- <p>We are looking for an experienced Senior Databricks Engineer to support enterprise data initiatives. This Long-term Contract position will focus on building and enhancing scalable data solutions, including extracting data from ServiceNow and structuring it for downstream ARDoc consumption within a broader enterprise architecture program. The role will partner with engineering, analytics, and platform teams to deliver reliable, governed, and high-performing data pipelines on Databricks.</p><p><br></p><p>Responsibilities:</p><p>• Develop and maintain robust data pipelines in Databricks using Apache Spark to support enterprise reporting and analytical use cases.</p><p>• Extract and transform data from ServiceNow, then create and manage structured tables that supply ARDoc as part of a larger architecture initiative.</p><p>• Design layered data models using Delta Lake practices to improve scalability, data usability, and long-term maintainability.</p><p>• Configure and manage Databricks jobs, workflows, and compute resources to improve processing efficiency and platform stability.</p><p>• Investigate performance issues across Spark workloads and implement tuning strategies that improve speed, reliability, and cost control.</p><p>• Establish data governance practices through cataloging, lineage visibility, and secure access controls within the Databricks environment.</p><p>• Work closely with data scientists, analysts, and platform teams to deploy production-ready data assets and support advanced analytics needs.</p><p>• Provide technical guidance to other engineers by promoting engineering standards, reviewing designs, and sharing platform best practices.</p>
- 2026-06-08T00:00:00Z