Data Integration Specialist

Description

Overview

Be part of something big: help unify data across multiple university systems as a key contributor to a major higher education initiative. You'll play a critical role in consolidating data across multiple higher education systems using your expertise in data schemas to map, transform, and validate data, ensuring every piece is accurate, consistent, and ready to power smarter decisions. The broader aim is to provide colleges and universities with technology tools that will make their data ready for analyses to support student outcomes.

Reporting to the Director, Research, this role is a chance to work on a forward-thinking, high-impact project alongside a collaborative, driven team, while building hands-on experience that will set you apart in the field. If you're passionate about data and eager to make a real difference in higher education, we want to hear from you.

What You’ll Do

• Perform comprehensive data mapping and execute transformations to build a unified data model for a higher education product.
• Work extensively with higher education system schemas and databases, primarily from ed tech platforms.
• Review, prioritize, and analyze data columns from various ed-tech systems, such as SIS and LMS platforms for inclusion in the integrated data model.
• Using higher education data, evaluate and validate data mappings and transformations to ensure accuracy and consistency at every step.
• Contribute to advanced data transformation processes that enable mapping across schemas, including splitting or concatenating data fields and applying filtering and if-then logic before populating target data fields.
• Support data quality assurance efforts using tools like dbt and Great Expectations.
• Collaborate closely with cross-functional teammates and external users to understand data needs and ensure the final data model meets real-world operational requirements.
• Attend calls and video meetings as required to support your scope of work.

Qualifications

Required

• Deep alignment with DataKind's mission and values and demonstrated commitment to educational equity and data-driven social impact.
• The ability to translate data from one structure to another, including spotting fields that only partly match, places where meaning gets lost, and fields that need to be split or merged. 
• Skill in writing data dictionaries and mapping specifications, and in tracking where data came from, so every transformation is traceable and repeatable. 
• Related to the above, experience with data architecture and governance as a foundation for producing insights from institutional data.
• Direct experience working with higher education data schemas and databases, including data from student information systems (SIS), Learning Management Systems (LMS), and related ed-tech platforms.
• Strong understanding of data transformations and checks of data quality.
• Proven ability to review and prioritize data columns across multiple systems for integration.
• Familiarity with SQL and Python.
• Strong project and time management skills, including the ability to gauge how long a task will take, keep deadlines on track, and communicate with team members about deliverables.

Preferred

• Familiarity with Agile methodologies.
• Ability to use Git for version control.
• Proficiency in Python and SQL.
• Experience with complex data transformation tools such as dbt and data validation frameworks like Great Expectations.
• Prior experience in higher education data environments or data integration firms.

About DataKind

At DataKind, we believe in the transformative power of data science and AI to create a more promising future. Since our founding in 2012, we've been at the forefront of designing scalable, data-driven tools that address some of the world's toughest challenges—ranging from frontline health, humanitarian action, climate and environment, economic opportunity, education, and more. As both a product innovator and a movement catalyst, we set new standards in the social sector, empowering organizations to harness the full potential of data science and AI while putting communities first.