SQL Data Engineer

Parra Consulting Group (PCG) is seeking a SQL Data Engineer to support federal health programs, regulatory science, and other high-impact missions. This position designs, develops, and optimizes scalable data solutions using advanced SQL and Databricks to deliver reliable insights that support mission-critical decisions. This successful candidate will be responsible for the following: - Design, develop, and optimize scalable data pipelines, data models, and analytics-ready datasets using advanced SQL and Databricks. - Develop, tune, and troubleshoot complex SQL solutions, including queries, stored procedures, views, and functions, across Oracle SQL, PostgreSQL, and Databricks SQL. - Integrate data from databases, cloud data platforms, APIs, JSON, XML, and flat files. - Implement automated testing, data validation, data reconciliation, and data-quality processes. - Translate solutions across different SQL dialects and database environments. - Collaborate with data engineers, analysts, software developers, data scientists, and client stakeholders to deliver secure, high-performing solutions. - Communicate technical concepts to technical and non-technical audiences, and raise questions, risks, and recommended actions to management early. Required Qualifications - Bachelor’s degree in Computer Science, Data Science, Engineering, Statistics, Biostatistics, or Mathematics. - 5+ years of experience developing, optimizing, and troubleshooting complex SQL solutions. - Ability to obtain and maintain a Public Trust or Suitability/Fitness determination based on client requirements. - S. citizenship required to support this federal contract. Required Experience - Experience developing, optimizing, and troubleshooting complex SQL solutions, including queries, stored procedures, views, functions, and data transformations, in Oracle SQL, PostgreSQL, and Databricks SQL. - 2+ years of experience with Databricks, including Databricks Workspace, notebooks, jobs, workflows, Apache Spark, Delta Lake, and cluster configuration. - Experience with relational databases, data modeling, dimensional modeling, data warehousing, and designing and implementing medallion architecture patterns. - Experience integrating data from databases, cloud data platforms, APIs, JSON, XML, and flat files. - Experience developing data engineering solutions in Python and managing code through Git or comparable source-control tools. - Experience implementing automated testing, data validation, data reconciliation, and data-quality processes. - Ability to work independently in an Agile, collaborative, and client-focused environment and troubleshoot complex issues. Preferred Qualifications - Experience with advanced Databricks capabilities, including Delta Live Tables, Workflows, and Unity Catalog. - Experience developing and optimizing ETL and ELT transformation workflows supporting reporting, analytics, or operational systems. - Experience with Pentaho or equivalent data integration and ETL tools. - Experience implementing CI/CD pipelines, automated deployments, and software development practices for data solutions. - Experience applying AI-enabled tools or techniques to improve data engineering workflows, pipeline performance, or developer productivity. - Experience with data governance, metadata management, data lineage, privacy, security, and access controls. - Experience supporting federal health data systems, regulatory science, or other regulated data environments. - Databricks, AWS Cloud, or data engineering technical certification. Originally posted on Himalayas