> Markdown version of [/jobs/ext/3992993-etl-data-engineer](https://www.wearedevelopers.com/jobs/ext/3992993-etl-data-engineer). 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). --- # ETL/Data Engineer - **Company:** ActioNet, Inc. - **Location:** Suitland-Silver Hill, MD, United States - **Contract:** Permanent contract - **Skills:** Agile Methodology, Big Data, Capability Maturity Model Integration, Signals Intelligence, Cyber Security, Data Centers, Data Integration, Data Transformation, Data Structures, Data Warehousing, Database Development, PostgreSQL, Query Optimization, Cloud Services, Software Engineering, SQL Stored Procedures, Data Processing, Information Technology Outsourcing, C4ISR, Data Ingestion, Database Optimization, Database Performance, Information Technology, Devsecops - **Published:** October 28, 2026 - **Apply:** https://jobs.jobvite.com/actionet/job/ox01AfwS/apply ## About the Role * U.S. citizenship required. * Ability to obtain and maintain a Public Trust determination. * Strong experience with PostgreSQL, including functions, stored procedures, and complex SQL development. * Demonstrated expertise in data warehousing, including schema design, data transformation, and reporting table development. * Experience automating data processing and managing large-scale data workflows. * Proficiency in database performance tuning, indexing strategies, and query optimization. * Experience with large-scale data aggregation and blending data from multiple sources. * Knowledge of foreign tables, external data ingestion, and data integration techniques. * Ability to design analytics-driven data structures that support complex reporting requirements. * Strong analytical, troubleshooting, and problem-solving skills., * Experience supporting high-volume government data programs or large-scale statistical data processing. * Familiarity with Decennial Census or Economic Census data workflows. * Experience optimizing PostgreSQL environments for large datasets and demanding reporting workloads. * Experience developing scalable data warehouse solutions in complex enterprise environments., As an ActioNeter, you get to be part of an exceptional team and a corporate culture that nurtures mutual success for our customers, employees, and communities. We give you the tools to be successful; all you need to do is bring your best ideas, your energy, and a desire to develop your skills, experience, and career. Are you ready to make a difference? ## Description ActioNet is seeking a ETL/Data Engineer to support high-volume data processing, warehousing, and reporting initiatives for Decennial and Economic Census (ECON) workflows. This role will focus on transforming raw data from staging environments into warehouse schemas and developing robust reporting detail tables to support analytics and operational reporting. The ideal candidate has strong PostgreSQL development skills, experience with large-scale data aggregation and multi-source data integration, and expertise in database performance tuning and optimization. Responsibilities * Process and transform raw data from staging environments into structured data warehouse schemas. * Design, develop, and maintain detailed reporting tables to support Decennial and ECON data workflows. * Build and optimize complex PostgreSQL functions, stored procedures, and automated data processing routines. * Perform large-scale data aggregations and integrate data from multiple sources to support reporting and analytics requirements. * Implement and manage foreign tables and external data ingestion processes. * Optimize database performance through indexing strategies, query tuning, and execution plan analysis. * Develop scalable, reliable, and efficient data processing solutions to support high-volume workloads. * Collaborate with technical teams and stakeholders to translate data and reporting requirements into effective database solutions. * Identify performance bottlenecks and implement improvements to data processing efficiency, scalability, and reliability.