Database ProgrammerAnalyst

The Database Programmer / Analyst will support the Philadelphia Citizens Police Oversight Commission (CPOC) Data Division with implementation and ongoing maintenance of data pipelines into and out of a PostgreSQL database. The role focuses on writing and maintaining scripts and queries that enable reliable data ingestion, extraction, and preparation for reporting and analysis. The position is hands-on and execution-oriented, emphasizing system organization, clarity, and repeatability rather than database administration, security, or advanced analytics. Work activities: Develop and maintain Python scripts to retrieve data from APIs and other external sources and load it into PostgreSQL Write and maintain SQL queries, tables, and views to support reporting and analysis Prepare and structure data for use in dashboards and advanced analytics Perform basic data validation and transformation to address formatting, consistency, and completeness issues Organize scripts, queries, and documentation to ensure maintainability and ease of handoff Document data sources, processing logic, and manual execution steps Troubleshoot data flow issues and support downstream users as needed Required Demonstrated experience writing SQL for PostgreSQL or similar relational databases Experience with Python scripting for data processing and API interaction Familiarity with moving data between systems (ingestion, transformation, extraction) Experience supporting reporting or analytics tools (e.g., BI platforms or statistical software) Ability to write clear documentation and maintain organized codebases Comfort working in a manual, script-driven execution environment Strong interpersonal skills, including the ability to work on teams and collaborate with colleagues, partners, and members of the public. Highly Desired/Preferred Experience working with Metabase or comparable BI/dashboarding tools Experience supporting or collaborating with R-based analytics workflows Familiarity with REST APIs and common authentication methods Experience maintaining small-to-medium data pipelines over time Prior work in environments with limited automation or evolving data practices

Created: 2026-03-10