Senior Data Engineer - ETL | Data Integration in New York at Jobgether
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Job Description
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Engineer - ETL | Data Integration based in United States.
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.
- 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.
- 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.
- 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.