Senior Data Engineer - ETL | Data Integration

JerseySTEM is seeking experienced Data Engineers to stabilize and scale core data pipelines that power analytics and reporting. The current platform complexity requires ownership from engineers who can design, implement, and maintain production grade workflows across multiple data sources. This role focuses on operational reliability, sound data modeling, and long term platform sustainability. Responsibilities Pipeline Engineering: Designing, configuring, and monitoring production grade ETL/ELT pipelines to ingest unstructured and structured data from third party data sources into our MySQL operational data warehouse using integrate.io, Google Apps Script/JavaScript. Security & Access Governance: Defining and auditing data access permissions, ensuring security guardrails are maintained as user access privileges rotate. API Management: Writing and debugging custom scripts and database queries to interact with native platform APIs. Data Mapping & Classification: Normalizing and mapping complex, disparate schemas from Salesforce CRM, iCIMS talent data, and Jira ticketing systems, and others. Design and maintain analytical models including fact and dimension tables. Operational Resilience: Manage schema changes, late arriving data, and source inconsistencies. Ensure data quality, consistency Provide technical leadership and define data integration best practices and standards Qualifications FIVE or more years of hands on experience in data engineering or data platform roles Technology requirements: Google Apps Script/JavaScript, Integrate.io or similar ETL platforms, mySQL, Python Proven experience integrating external APIs and third party systems Deep understanding of dimensional modeling and warehouse architecture Ability to operate independently in a remote environment and own pipelines end to end What Success Looks Like ETL pipelines are stable, incremental, and predictable API ingestion runs with minimal manual intervention Data models are trusted and analytics ready Analytics teams focus on insights rather than resolving data issues JerseySTEM