Strada Education Foundation

Associate Client Data Engineer

Washington, DC

Sponsorship not specified$75k-$92kDetected 13 days ago

PythonData StructuresGitSQLPostgreSQLSnowflakeRedshiftAWSPandasAirflowdbtData AnalysisData EngineeringData ScienceCybersecurityResearchCommunication

About the role

As an Associate Client Data Engineer at CredLens, you will focus on the client-onboarding workflow that brings new credential-issuer data into our platform.
Because so much of the work involves direct client interaction, excellent customer-service skills and clear communication are essential.
This is a hybrid role requiring in-person attendance at the office at least two days a week, likely Tuesdays and Thursdays.

Receive incoming client data and perform exploratory data analysis to understand its structure, quality, and completeness.
Clean, transform, and validate client data so it conforms to CredLens' standards and is ready for downstream ingestion.
Build and run the models and transformations that move a client's data through the onboarding stages of the pipeline, using SQL, Python, DBT, and Airflow.
Document each client's onboarding: data sources, decisions made, and any exceptions, contributing to shared onboarding procedures and templates.
Work with the broader Data Engineering team to research, learn, and implement new improvements to the onboarding pipeline's efficiency & scalability so it can grow with us.
Demonstrated alignment with CredLens' guiding values, commitment to building a strong and healthy workplace culture, and working in a collaborative environment.

CredLens is building a nonprofit national data trust focused on verified outcomes for non-degree credentials.
CredLens is designed to fill the data gap for non-degree credentials.
Strong customer-service orientation and the ability to communicate clearly with non-technical clients.
Experience with Pandas DataFrames, Jupyter notebooks, and other quick data processing tools.
Familiarity with DBT, Airflow, or other data pipeline and orchestration tooling.
Familiarity with AWS S3 and Lambda functions, or other AWS services.
Core responsibility areas, listed below with the approximate time required for execution in the first 12 - 18 months of work if the incumbent is new to the role:
Suitable for a new or recent graduate; no prior professional experience required.
Attention to detail, particularly around data quality, validation, and documentation.
Consistently takes initiative to learn and try new things, and keeps a mindset of constant improvement.
Exposure to Redshift, Snowflake, PostgreSQL, or similar databases.

data sources, decisions made, and any exceptions, contributing to shared onboarding procedures and templates.
Track onboarding progress and time, and surface areas of friction to improve the process so that it becomes faster and more repeatable over time.
Bachelor's degree in computer science, information systems, data science, or a related field is required.
OR, equivalent practical experience is required, at least two years.
Experience Required
Suitable for a new or recent graduate
no prior professional experience required.
Internships, academic projects, or other hands-on data work are a plus, as is a demonstrated ability to learn quickly.

Data cleaning & manipulation
Non-degree credentials are reshaping how people move from learning to earning.
Millions of learners are pursuing certificates, bootcamps, and workforce programs as pathways to better jobs and higher wages.
But growth has outpaced clarity.
Thousands of offerings, uneven definitions, and fragmented outcomes data make it nearly impossible to distinguish impact from activity.
CredLens exists to fix that.

Diversity, equity, and inclusion are central to CredLens' organizational vibrancy, employee experience, and mission.

This listing is sourced directly from Strada Education Foundation's careers page and normalized into a canonical job model.