DataKind is looking for a Data Engineer!

DataKind is looking for a values-driven, client-facing data engineer who is ready to make a major impact on student graduation rates by building and maintaining data pipelines in close partnership with higher education institutions. If you're a technically strong problem-solver who genuinely enjoys working with people, can hold down the technical side of a client engagement independently, and are committed to advancing equity through data — we want to bring you on board!

Location

This is a remote position that can be based anywhere in the U.S. and requires the majority of working hours each day to fall between 8am and 6pm Eastern Standard Time.

This position requires travel across the United States, expected at about 20% of working days, mostly on-site at higher education institutions to provide direct technical support.

This role reports to the Data Science Manager and sits within the Data Science team.

Salary Range
The salary range is $106,000 - $120,000.

Actual salary within these ranges will be based on the candidate’s experience and internal salary equity scan of active employee(s) with similar role and experience.

About the Opportunity

DataKind is seeking a Data Engineer to lead the technical work that makes our UDTS platform — an end-to-end data platform for higher education — genuinely useful to the institutions we serve. This role sits at the intersection of data architecture, engineering, and client partnership, enabling educational institutions to use AI and advanced analytics to improve student outcomes equitably.

Reporting to the Senior Data Science Manager, you'll work across two complementary tracks: building and maintaining the infrastructure that powers UDTS, and going on-site with partner institutions to get their systems connected, configured, and delivering value to their teams. You'll collaborate closely with Engineering, Data Science, Customer Success, Research, and Product — and you'll often be the sole technical voice in the room with a client.

What You’ll Do

Partner Data Enablement (40%)

Lead the technical onboarding of partner institutions onto UDTS, designing and building the integrations (APIs, pipelines, etc.) needed to connect their existing data systems for seamless ingestion.
Collaborate on-site with institutional data teams to configure and customize UDTS front-end dashboards — working through requirements like which fields to surface, how data should aggregate, and how to make the platform most relevant to each institution's specific workflows and users.
Support institutions in securely sharing data and implementing governance protocols.
Communicate technical requirements, timelines, and processes with external partners in accessible, solutions-oriented ways — and bring the patience and people skills to make those conversations productive.

Data Architecture and Engineering (40%)

Design, build, and maintain scalable data pipelines and architectures to support education-focused data products.
Develop robust APIs and integrations to facilitate seamless data exchange across multiple institutional systems and data providers.
Optimize data ingestion, transformation, and validation processes for reliability, transparency, and performance.
Ensure all data systems comply with DataKind’s governance, privacy, and security standards.
Produce clear, reusable code and comprehensive documentation for both technical and non-technical audiences.

Collaborate and contribute across DataKind (20%)

Collaborate with team members within the technology team to set engineering standards and guide data infrastructure strategy.
Partner with data engineers and scientists to operationalize models and analytics pipelines into production-ready systems.
Collaborate with Customer Success, Research, Product, and Implementation teams to ensure technical design aligns with user and partner needs.
Contribute to the continuous improvement of internal tooling, workflow automation, and best practices.

Qualifications

Required

Deep alignment with DataKind's mission and commitment to educational equity and data-driven social impact
Degree in Computer Science, Data Engineering, Information Systems, or related technical field (or equivalent professional experience).
At least 4 years of professional experience in data engineering, including experience leading client-facing solution architecture or infrastructure design (e.g., solutions engineering, implementation engineering).
Advanced proficiency in Python, SQL, and one or more cloud platforms (preferrably GCP).
Demonstrated experience with Databricks, or comparable data intelligence platforms.
Deep understanding of ETL/ELT pipelines, data warehousing, and data orchestration tools.
Knowledge of data governance, privacy, and security frameworks in regulated or educational environments.
Proven ability to collaborate effectively with data scientists, software engineers, data engineers, data analysts, and product managers.
Solid understanding of Software Engineering principles and the data science project life-cycle
Excellent communication skills — including the ability to translate complex technical topics for non-technical audiences and to work productively with data practitioners at partner institutions.
Comfort operating as the primary technical resource in a client setting, with an account manager present for relationship support but relying on you for all things technical.
Genuine enjoyment working with people, self-motivated, results-driven, and persistent in the face of challenges.

Preferred

Experience with education data systems (e.g., SIS, LMS, or student outcome data).
Building, maintaining, and customizing dashboards for varied end users.
Comfort with JavaScript.
Experience integrating data from SaaS providers and APIs at scale.
Strong technical writing and documentation for both internal and partner use.
Familiarity with civic tech, social impact, or nonprofit data ecosystems.

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.

Why Work with DataKind

At DataKind, we believe that people are the most important asset to delivering on our mission. As a people-first remote organization, we offer the following for all our employees:

Flexibility and time off. Enjoy genuine flexibility that goes beyond adjustable hours. We build in shared time off, organization-wide recharge days, bi-weekly meeting-free days, and flexible PTO (with a minimum of 20 vacation days encouraged annually).

Comprehensive Wellness Support. We care for your total wellbeing with 100% employer-paid medical, vision, and dental benefits for employees (72% for dependents), a wellness reimbursement program for the activities and purchases that matter to you, and 12 weeks paid parental leave when you need it most.

A Culture of Growth. Every team member receives professional development funding each year, alongside mentorship and advancement opportunities. We invest in your future with a 401(k) plan with 5% employer matching.

Meaningful Connection. Despite being distributed across time zones, we value being able to come together in person for conferences, strategic planning, and at our annual staff retreat.

Living our Values. DataKind is committed to a diverse, equitable and inclusive work environment in our day-to-day work and via special initiatives driven by our DEI Steering Committee.

DataKind is an Equal Opportunity Employer

DataKind is an equal opportunity employer and strongly encourages candidates from underrepresented groups in tech to apply. DataKind does not discriminate on the basis of race, color, gender, disability, religion, national origin, age, sexual orientation, genetic information, pregnancy, or any other protected category.

Applicants must have a U.S.-based permanent address and be currently authorized to work in the United States on a full-time basis indefinitely without employer visa sponsorship.