Part-time Data Engineer

TNTP is the nation's leading education nonprofit that integrates research, policy, and consulting to support young people's aspirations. The Part-time Data Engineer will design, develop, and maintain data infrastructure, ensuring data is accessible and optimized for decision-making across the organization.

Responsibilities:

• Design and develop scalable data pipelines that retrieve information from multiple sources, convert it to the required format, and store it in suitable data repositories optimized for performance, scalability, and efficiency
• Develop and optimize data transformations that prepare data for analytics, AI, and machine‑learning use cases, including feature engineering and workflow automation
• Optimize data systems by tuning performance, resolving bottlenecks, and applying caching and indexing to improve queries
• Ensure data consistency, accuracy, and completeness by implementing validation, monitoring, and automated data quality checks within pipelines
• Partner with analysts, data scientists, and business stakeholders to understand data requirements and deliver data products that support strategic and operational decision‑making
• Collaborate with the Director of Data Architecture & Engineering to implement and evolve data modeling, architectural, and governance standards
• Improve the quality, security, and usability of analytical models by partnering with data scientists and analysts on upstream data design
• Contribute to the development and maintenance of data documentation, metadata, and data dictionaries
• Support adoption of modern data tools and platforms by enabling best practices and shared patterns across teams
• Participate in the implementation of data governance policies by embedding standards, controls, and lineage into data pipelines and platforms

Requirements:

• Bachelor's degree in computer science, data science, business, technology, or related field (or equivalent experience)
• 3+ years of hands‑on experience designing, building, and maintaining data pipelines and data platforms in production environments
• Strong proficiency in SQL, Python or R for data transformation, analysis, and pipeline development
• Experience designing and implementing cloud‑based data architectures using modern data warehouses such as Snowflake or Databricks
• Experience working with relational and non‑relational data stores (e.g., SQL, NoSQL)
• Experience building data solutions that support analytics, business intelligence, and AI/ML use cases
• Familiarity with data quality, reliability, and governance practices, including validation, lineage, and access controls
• Ability to collaborate within and across teams of different technical knowledge to support delivery and educate end users on data products
• Strong problem‑solving and debugging skills, with the ability to diagnose issues in complex data systems
• Ability to clearly communicate technical concepts and tradeoffs to technical and non‑technical audiences
• Prior experience with Workday and Salesforce is highly preferred
• Reporting certifications in either system is a plus