Data Engineer

American Public Media Group•Saint Paul, MN

11h•$105,000 - $112,000•Hybrid

About The Position

The Data Engineer is a core member of the APMG Technology team, responsible for building and maintaining data pipelines, integrations, and models that power the organization’s reporting and operational systems. Working within a small, high-impact team, this role contributes directly to APMG’s data ecosystem — spanning Azure cloud infrastructure, Salesforce NPSP, and a range of integrated SaaS platforms. The Data Engineer partners closely with the Data Architect to translate business requirements into durable, well-tested data solutions, and brings a pragmatic, curious mindset to solving complex integration and modeling challenges. This role operates with meaningful autonomy and is expected to take ownership of assigned pipelines and domains end-to-end — from design through deployment and monitoring. As a member of a lean team, the Data Engineer also contributes to peer learning, documentation, and the ongoing improvement of team practices, including the use of AI-assisted development tooling to increase velocity and code quality.

Requirements

Bachelor’s degree in Computer Science, Information Systems, or a related field, or equivalent professional experience
3–5 years of hands-on experience in a data engineering, analytics engineering, or similar role
Proficiency in SQL, including complex query writing, stored procedures, and performance tuning in a relational database environment (SQL Server preferred)
Proficiency in Python for data engineering tasks, including scripting, API consumption, transformation logic, and testing
Experience designing and maintaining data models for analytical or operational use cases
Experience building and consuming REST APIs and integrating data across disparate platforms
Hands-on experience with Azure cloud services, including Azure Data Factory or equivalent pipeline tooling and Azure SQL
Demonstrated experience writing and maintaining automated tests for data pipelines and transformation logic
Experience delivering within an agile development process, including writing user stories, acceptance criteria, test plans for general data engineering and analytics requirements
Ability to understand business requirements and translate them into sound data solutions
Strong attention to detail and a commitment to data quality and accuracy
Ability to work independently and collaboratively in a small, cross-functional team environment
Clear written and verbal communication skills, with the ability to explain technical concepts to non-technical stakeholders
Self-directed learner with a genuine interest in evolving tooling, practices, and technologies
Comfort operating with some ambiguity and finding effective solutions within resource and time constraints
Embraces APMG organizational values, including EIDA (Equity, Inclusion, Diversity, and Accessibility)

Nice To Haves

Experience with AWS services (e.g., S3, RDS, DynamoDB, Lambda) and cross-cloud pipeline patterns
Familiarity with the use cases and trade-offs of different data storage paradigms, including relational databases, document stores, data warehouses, and lakehouse architectures
Familiarity with Salesforce data structures, particularly NPSP (Nonprofit Success Pack)
Experience with Power BI, including dataset development and DAX
Familiarity with other cloud-based data platforms and tools, including Databricks, DBT, data catalogs, etc.
Working experience with AI-assisted development tools (e.g., GitHub Copilot, Claude, Cursor) to accelerate and improve engineering work
Experience with identity resolution patterns or working with systems that use multiple identifiers across platforms
Familiarity with nonprofit, public media, or fundraising data domains
Exposure to data governance practices, data cataloging, or metadata management
Experience with version control (Git) and CI/CD workflows for data pipelines

Responsibilities

Design, build, and maintain data pipelines and ETL/ELT workflows using Azure Data Factory and related Azure services
Develop and maintain data models in the Azure SQL-based Enterprise Data Warehouse, ensuring performance, integrity, and alignment with organizational standards
Write clean, well-tested Python and SQL code to support ingestion, transformation, and integration tasks
Build and maintain API integrations between internal systems and third-party SaaS platforms (e.g., Salesforce NPSP, donation gateways, media systems)
Implement automated testing for data pipelines and transformations to ensure reliability and catch regressions early
Monitor pipeline health, respond to data quality issues, and maintain alerting and logging practices
Collaborate with the Data Architect to implement and adhere to organizational data standards, naming conventions, and governance practices
Contribute to Power BI reporting by maintaining underlying data models and ensuring accurate, performant dataset availability
Document pipeline logic, data models, and integration specifications to support knowledge sharing and maintainability
Participate in code reviews and contribute to a culture of technical rigor and continuous improvement
Leverage AI-assisted development tools to accelerate implementation, improve code quality, and explore new solutions
Provide secondary support for business application systems as needed within a collaborative team environment
Other duties, as assigned