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Association of American Medical Colleges

Senior Data Engineering Specialist

Data EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USA$127.5k - $150k

About the Job

Requirements

  • A bachelor's degree in Computer Science, Data Engineering, or a related field is required; related work experience may substitute in some positions, with one year of accredited college coursework equivalent to one year of related work experience.
  • At least five years of progressively responsible experience in data engineering or a closely related field is required.
  • At least one year of hands-on experience with AWS data services such as AWS Glue, Amazon S3, and Lambda, and familiarity with Snowflake or similar cloud-based data warehousing solutions.
  • Experience designing and building modern, scalable data pipelines in production environments.
  • Experience contributing to data projects as part of cross-functional teams and collaborating with peers and stakeholders to deliver technical solutions.
  • Familiarity with data governance and compliance best practices and 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.

Responsibilities

  • Develop, maintain, and support an enterprise data warehouse system and corresponding data marts; evaluate and incorporate existing subject areas into an enterprise model.
  • Review data loaded into the data warehouse for accuracy, troubleshoot and tune existing applications, and research new data warehouse applications for potential adoption.
  • Create new or enhanced data warehouse components and assist in establishing development standards.
  • Design, implement, and maintain complex databases, including considerations such as access methods, access time, device allocation, validation checks, organization, protection, security, documentation, and statistical methods.
  • Analyze organizational business processes and systems, including financial, logistical, and human resources systems, and automate or optimize processes through third-party enterprise resource planning systems such as SAP, PeopleSoft, or Oracle.
  • Create, update, implement, and model best practices independently; lead projects or project steps and remain accountable for ongoing project, program, or operational activities.
  • Solve complex problems independently, offer solutions, act as a resource for less experienced colleagues, represent the team in meetings with other work units, and serve as a resource for management.
  • Architect, develop, and manage robust, scalable ETL/ELT data pipelines to provide accurate, timely, and reliable data flow for downstream data use, analytics, and reporting.
  • Build and refine data models, warehouses, and Lakehouse architectures to support efficient storage, processing, and retrieval in alignment with enterprise data strategies.
  • Implement validation frameworks, monitoring, and testing strategies to ensure data consistency, completeness, and reliability across the data lifecycle.
  • Partner with development teams, analysts, product managers, and business stakeholders to understand data needs and deliver solutions that support decision-making and innovation.
  • Identify opportunities to automate repetitive operational tasks and stay informed about data platform features, including Snowflake, AWS Glue, and Airflow.
  • Suggest and contribute to improvements in pipeline design, monitoring, and alerting, and participate in training and cross-skilling opportunities.
  • Ensure data solutions comply with internal policies and applicable security and governance controls.
  • Provide technical leadership, coaching, and code reviews for junior engineers and peers to promote development and engineering best practices.

Desired Qualifications

  • Designing and implementing modern, scalable data pipelines.
  • Leading technical projects or initiatives in cross-functional teams.
  • Mentoring junior engineers or contractors.
  • Adhering to data governance and compliance frameworks.
  • Contributing to long-term platform or tooling strategy.
  • Experience with large-scale ETL/ELT pipelines across complex data systems.
  • AWS or Snowflake certifications.

About the Company

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