Senior Data Engineering Specialist

Why us, why now?

Works in a data warehouse environment which includes data design, database architecture, metadata and/or repository creation. Reviews data loaded into the data warehouse for accuracy. Responsible for the development, maintenance, and support of an enterprise data warehouse system and corresponding data marts. Evaluates existing subject areas stored in the data warehouse.

Incorporates existing subject areas into an enterprise model. Troubleshoots and tunes existing data warehouse applications. Conducts research into new data warehouse applications and determines viability for adoption. Assists in establishing development standards. Creates new or enhanced components of the data warehouse.

May design, implement, and maintain complex databases with respect to JCL, access methods, access time, device allocation, validation checks, organization, protection and security, documentation, and statistical methods.

May analyze organization business processes and systems (financial, logistical, human resources, etc.) and automate/optimize processes through a third party enterprise resource planning system (ERP - e.g. SAP, PeopleSoft, Oracle). Works independently to create, update, implement and model best practices.

Leads projects or project steps of varying size and has accountability for ongoing activities related to projects, programs and/or operations. Applies in-depth professional level knowledge to independently solve a full range of complex problems and offers sensible solutions. Acts as a resource for colleagues with less experience. Represents team in meetings with other work units. Serves as a reliable resource for management.

How you will make an impact?

Design and Maintain Scalable Data Pipelines

• Architect, develop, and manage robust and scalable ETL/ELT data pipelines to ensure accurate, timely, and reliable data flow across systems, enabling effective downstream data utilization, analytics and reporting.

Develop and Optimize Data Architecture

• Build and refine data models, warehouses, and Lakehouse architectures to support efficient data storage, processing, and retrieval, aligning with enterprise data strategies.

Ensure Data Quality and Integrity

• Implement validation frameworks, monitoring, and testing strategies to ensure data consistency, completeness, and reliability across all stages of the data lifecycle.

Collaborate with Cross-Functional Teams

• Partner with peer development teams, analysts, product managers, and business stakeholders to understand data needs and deliver solutions that support decision-making and innovation.

Lead Technical Implementation of Data Projects

• Identify opportunities to automate repetitive operational tasks to improve efficiency, while staying informed of new features in cloud and on-premise data platforms such as Snowflake, AWS Glue, and Airflow.
• Suggest and contribute to process improvements in pipeline design, monitoring, and alerting, and actively participate in training and cross-skilling opportunities to strengthen technical expertise.

Manage Data Security and Compliance

• Ensure data solutions comply with internal policies, adhering to security and governance controls where necessary.

Mentor and Guide Team Members

• Provide technical leadership, coaching, and code reviews for junior engineers and peers to promote skill development and uphold engineering best practices.

Minimum Education

Bachelor's degree in Computer Science, Data Engineering, or related field.

Minimum Experience of Related Work

5 - 7 years of related work experience

• A minimum of five (5) years of progressively responsible experience in data engineering or a closely related field is required to independently perform the essential duties of this position.
• Minimum of 1 year 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 designing and building modern, scalable data pipelines in production environments.
• 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.

Preferred Experience

• 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

Certifications: AWS/Snowflake certifications are preferred but not required.

Remote Work Eligibility

This is a remote-eligible position at AAMC. Candidates may reside anywhere within the contiguous United States, excluding California, Massachusetts, New York, and Oregon.

Pay and benefits

Multiple factors are taken into consideration to arrive at the final hourly rate/annual salary to be offered to the selected candidate. Factors may include, but are not limited to, the scope and responsibilities of the role, the selected candidate's work experience, education and training, as well as internal equity, market, and business considerations.

If a bachelor's degree is required, related work experience may be substituted in some positions. One year of college course work at an accredited institution is equivalent to one year of related work experience.

Please attach a resume as part of the application process. It is important that files DO NOT include periods (.) within the file name.

Browser Requirements

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