Description:
As a Part-time Data Engineer on the enterprise Data and Analytics team, you are responsible for designing, developing, and maintaining the critical infrastructure for storing, processing, and analyzing data. You'll create pipelines that enable efficient and reliable integration, transformation, and delivery of data throughout the enterprise. Working alongside the Director of Data Architecture & Engineering, as well as collaborating with analysts, data scientists, and other business stakeholders, you help make sure data is accessible, trustworthy, and optimized for informed decision-making.
Specifically, You Will
- 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.
What You Bring
We expect our Part-time Data Engineer to bring:
- Love of data. You have a deep curiosity about how data moves, scales, and behaves in complex systems. You love breaking down messy, ambiguous data problems into clean, reliable, well‑structured components that others can trust and build on.
- Continuous improvement. You have a builder’s mindset and constantly look for opportunities to modernize. You seek better patterns, automate manual work, strengthen architecture, and improve reliability through thoughtful engineering practices.
- Commitment to data quality, reliability, and governance. You believe data reliability is engineered, not inspected. You design systems with built‑in quality checks, lineage, security, and governance, ensuring that data products meet defined contracts, SLAs, and organizational expectations.
- Security, privacy and equity orientation. You design solutions that honor privacy, protect sensitive information, and ensure data can be used responsibly across TNTP.
- Excellent documentation and communication skills. You document with clarity and communicate with clarity, making complex data systems usable, maintainable, and trustworthy for engineers, analysts, and stakeholders alike.
Qualifications
- 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.