The Data Engineer is responsible for designing, building, and maintaining the technical foundations of the USOPC’s enterprise data ecosystem. This role develops modern data solutions that combine scalable pipelines with flexible integrations, ensuring data flows seamlessly across systems and into platforms that power reporting, analytics, and operations. The engineer ensures that data is reliable, high-quality, and accessible, enabling both actionable insights and interoperability across the enterprise.

The ideal candidate will bring deep technical expertise in modern data engineering and integration practices, strong problem-solving skills, and the ability to collaborate with both technical and business stakeholders. This role is essential to advancing the USOPC’s enterprise data strategy and enabling data-driven decision making across the organization.

Architecture & Engineering Design, develop, and maintain efficient and scalable data pipelines and API-driven integrations that ingest, transform, and exchange data across enterprise systems, applications, and external partners. Build and maintain data models, schemas, and architectures to support analytical needs, reporting requirements, and operational integrations. Write high-quality code to architect custom, flexible integration frameworks for internal applications and third-party systems. Implement solutions leveraging ETL/ELT frameworks, orchestration tools (Airflow, dbt, Prefect), and integration patterns (batch, real-time, event-driven). Optimize pipelines, integrations, and data services for performance, scalability, and maintainability. Monitor pipeline and integration health; proactively troubleshoot data quality, delivery, or connectivity issues.

Data Quality, Governance, & Security Ensure accuracy, consistency, and reliability of both analytical datasets and transactional integrations through validation and monitoring frameworks. Implement robust error handling, reconciliation, and retry logic to maintain data integrity in system-to-system flows. Adhere to data governance, security, and compliance requirements, including authentication and authorization standards (OAuth, SAML, JWT). Partner with data owners and system owners to align on definitions, integration rules, and stewardship practices. Document pipelines, integrations, APIs, and architectures for maintainability and transparency.

Collaboration & Communication Partner with analysts, data scientists, system owners, and business stakeholders to deliver solutions that meet both analytical and operational integration needs. Translate business requirements into technical specifications for data pipelines and integrations. Provide consultation on data access, pipeline enhancements, system connectivity, and API usage. Participate in cross-functional initiatives to align engineering with enterprise data strategy and evolving business needs.

Innovation & Continuous Improvement Stay current on emerging data engineering and integration technologies (cloud platforms, APIs, middleware, event-driven frameworks). Identify opportunities to automate workflows, reduce manual data handling, and improve system interoperability. Pilot and evaluate new tools (e.g., Snowflake features, dbt, MuleSoft, Airbyte, Kafka) to improve delivery speed and reliability. Foster a culture of knowledge-sharing, reusability, and experimentation within the engineering team.