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