Senior Data Engineer - ETL | Data Integration

About the role

This is a hands-on data engineering opportunity focused on stabilizing and scaling production-grade data pipelines that support analytics and reporting. You will take ownership of complex integrations spanning multiple structured and unstructured data sources and operational systems. The role combines ETL/ELT engineering, API integration, data modeling, data quality, and platform reliability. You will design efficient incremental and change-data-capture workflows while ensuring data remains accurate, secure, and analytics-ready. Working independently, you will help establish scalable data integration standards and improve the long-term sustainability of the platform. Your work will directly enable analytics teams to spend more time generating insights and less time resolving data issues. This is a pro-bono volunteer role requiring a minimum six-month commitment of approximately six flexible hours per week.

Accountabilities

• Design, configure, monitor, and maintain production-grade ETL/ELT pipelines that ingest structured and unstructured data from third-party sources into a MySQL operational data warehouse using integrate.io.
• Implement change data capture (CDC) and incremental loading strategies to support efficient, reliable, and predictable data refreshes.
• Integrate external APIs and third-party systems, including developing and debugging custom scripts and database queries for native platform APIs.
• Normalize, map, and classify complex and disparate data schemas from systems such as Salesforce CRM, iCIMS, Jira, and other business platforms.
• Design, implement, and maintain analytical data models, including fact and dimension tables, to support reliable reporting and analytics.
• Manage schema changes, late-arriving data, source inconsistencies, and other pipeline challenges while maintaining data quality and consistency.
• Define and audit data access permissions and help ensure appropriate security guardrails remain in place as user access privileges change.
• Monitor pipeline performance and proactively identify and resolve reliability, data quality, and integration issues.
• Take end-to-end ownership of assigned data pipelines, from design and implementation through monitoring, troubleshooting, and continuous improvement.
• Provide technical leadership and establish data integration best practices, engineering standards, and sustainable development patterns.
• Build resilient workflows that minimize manual intervention and provide analytics teams with trusted, analytics-ready data.
• Contribute to the long-term scalability, operational resilience, and maintainability of the data platform.

Requirements

• Five or more years of hands-on experience in data engineering, data platforms, or a closely related technical field.
• Strong experience working with MySQL in analytical, data warehouse, or hybrid environments.
• Proven experience integrating external APIs and third-party business systems.
• Demonstrated experience implementing CDC, incremental loading, or comparable data synchronization patterns.
• Deep understanding of dimensional modeling, data warehouse architecture, and analytical data structures.
• Advanced SQL skills and strong proficiency in Python or a comparable programming language.
• Experience designing and maintaining production-grade ETL/ELT pipelines and data integration workflows.
• Strong understanding of data quality, schema management, source inconsistencies, and operational resilience.
• Ability to work independently, make sound technical decisions, and take full ownership of data pipelines from end to end.
• Strong problem-solving and troubleshooting capabilities with an emphasis on durable solutions rather than one-off fixes.
• Ability to establish technical standards, communicate best practices, and provide technical leadership in a collaborative environment.
• Comfortable working in a hands-on engineering role rather than a purely advisory or oversight position.

Benefits

• Pro-bono volunteer position with no salary or monetary compensation.
• Flexible commitment of approximately six hours per week.
• Minimum six-month membership commitment, providing an opportunity to contribute to a mission-driven STEM organization.
• Opportunity to apply advanced data engineering skills to meaningful technology and analytics initiatives.
• Hands-on ownership of production data pipelines, integrations, data models, and platform reliability.
• Opportunity to establish engineering standards and influence the long-term sustainability of a data platform.
• Professional networking opportunities through a community of pro-bono STEM professionals.
• A $100 refundable deposit is required for most members and is returned after six months of active membership.
• K–12 educators, retirees, veterans, interns, and students are exempt from the refundable deposit.