> Markdown version of [/jobs/ext/4675825-data-engineer-oracle-pl-sql-databricks-java-spark](https://www.wearedevelopers.com/jobs/ext/4675825-data-engineer-oracle-pl-sql-databricks-java-spark). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - Oracle PL/SQL, Databricks, Java & Spark - **Company:** Intuitive Insights LLC - **Location:** Houston, TX, United States - **Experience:** Expert - **Contract:** Contract - **Skills:** Unity 3d, Java (Programming Language), Amazon Web Services, Amazon S3, Business Logic, Data Warehousing, Jinja (Template Engine), Python (Programming Language), Oracle SQL Developer, Performance Tuning, Standard Sql, Scala (Programming Language), SQL Databases, Macros, Snowflake, Apache Spark, Spring-boot, Data Lakes, Kubernetes, Apache Kafka, Cloud Migration, Data Pipelines, Docker, Databricks - **Published:** November 11, 2026 - **Apply:** https://www.dice.com/job-detail/e4de12ff-1f27-47bc-9ee4-a55204ea6bee ## About the Role * Strong Oracle PL/SQL and SQL expertise. * Databricks, Databricks SQL, Delta Lake, and Unity Catalog. * Hands-on dbt experience, including models, snapshots, macros, Jinja, and testing. * Java, Python, Scala, and Spark experience. * Strong data modeling and performance optimization experience. * Legacy-to-cloud migration and data reconciliation experience. Preferred Skills: * AWS, S3, Snowflake, Dremio. * Spring Boot, Kafka, Kubernetes, and Docker. ## Description We are looking for an experienced Senior Data Engineer to support modernization of the Credit Risk technology stack., * Modernize and upgrade enterprise Credit Risk technology platforms. * Develop and maintain complex Oracle PL/SQL packages, procedures, views, and business logic. * Develop and optimize SQL and Databricks SQL queries. * Work with Databricks, Delta Lake, Unity Catalog, and dbt. * Develop data pipelines using Java, Python, Scala, and Apache Spark. * Implement dimensional data modeling, SCD2, and historical data tracking. * Perform Spark and Databricks performance tuning. * Support legacy-to-cloud data migration, reconciliation, and validation.