Data Engineering Specialist

Association of American Medical Colleges•Washington DC, DC

2d•Remote

About The Position

Data Engineer is a key role on a centralized data engineering team that supports a wide range of data applications across the organization. This role focuses on building and maintaining reliable, scalable data pipeline, ensuring consistent, high-quality data is available for both operational and analytical use. Working closely with cross-functional teams, the Data Engineer helps support data accessibility, integrity, and performance, enabling data-driven decision-making throughout the business.

Requirements

Bachelor’s degree in Computer Science, Data Engineering, or related field. Candidates without the specified degree may qualify with a demonstrated equivalent in professional experience and/or training.
2 - 4 years of related work experience
Typically requires 2 - 4 years of experience in data engineering or a related field, which may include relevant internships.
Candidates should demonstrate the ability to contribute to the development and maintenance of data pipelines in a professional setting.

Nice To Haves

Experience designing and building modern, scalable data pipelines in production environments.
Hands-on experience working with AWS data services such as AWS Glue, Amazon S3, Lambda, and other related tools, as well as familiarity with Snowflake or similar cloud-based data warehousing solutions.
Experience contributing as part of cross-functional teams on data projects, collaborating with peers and stakeholders to deliver technical solutions.
Familiarity with data governance and compliance best practices, with the ability to follow established frameworks.
Experience working on ETL/ELT pipelines within large or complex data systems, ensuring data quality and reliability.
Demonstrated ability to follow technical direction and contribute to ongoing platform and tooling improvements.
AWS/Snowflake certifications are preferred but not required.

Responsibilities

Build and Maintain Data Pipelines: Develop and maintain reliable data pipelines that move and transform data across systems to support business reporting, analytics, and operational processes.
Support Data Architecture and Modeling: Work with senior engineers and architects to implement data models and contribute to building efficient data warehouse and Lakehouse environments aligned with established architectural standards.
Ensure Data Quality Through Automated and Embedded Practices: Design and maintain data pipelines with built-in validation checks and automated monitoring to ensure data remains accurate, complete, and consistent throughout its lifecycle. Collaborate with the testing team to align on quality standards, while embedding data quality practices directly into development workflows.
Collaborate Across Teams: Engage with peer development teams, analysts, product managers, and business stakeholders to understand data requirements and help deliver data solutions that meet their needs.
Contribute to Data Project Delivery: Support the execution of data engineering tasks within larger projects, ensuring high-quality implementation under the guidance of senior/lead/principal engineers or project leads.
Ensure Data Governance and Security Compliance: Follow established data governance, security, and privacy standards, and assist in implementing controls that ensure compliance with organizational policies and regulations.