Sr. Data Engineer (Hybrid)

Sr. Data Engineer (Hybrid)

Chicago, IL

The American Medical Association (AMA) is the nation's largest professional Association of physicians and a non-profit organization. We are a unifying voice and powerful ally for America's physicians, the patients they care for, and the promise of a healthier nation. To be part of the AMA is to be part of our Mission to promote the art and science of medicine and the betterment of public health.

At AMA, our mission to improve the health of the nation starts with our people. We foster an inclusive, people-first culture where every employee is empowered to perform at their best. Together, we advance meaningful change in health care and the communities we serve.

We encourage and support professional development for our employees, and we are dedicated to social responsibility. We invite you to learn more about us and we look forward to getting to know you.

We have an opportunity at our corporate offices in Chicago for a Sr. Data Engineer (Hybrid) on our Information Technology team. This is a hybrid position reporting into our Chicago, IL office, requiring 3 days a week in the office.

As a Sr. Data Engineer, you will play a key role in implementing
and maintaining AMA's enterprise data platform to support analytics,
interoperability, and responsible AI adoption. This role partners closely with
platform engineering, data governance, data science, IT security, and business
stakeholders to deliver highquality, reliable, and secure data products. This
role contributes to AMA's modern lakehouse architecture, optimizing data
operations, and embedding governance and quality standards into engineering
workflows. This role serves as a
senior technical contributor within the team-providing mentorship to junior
engineers and implementing engineering best practices within the data platform function,
in alignment with architectural direction set by leadership.

RESPONSIBILITIES:

Data Engineering & AI Enablement

• Build and maintain scalable data pipelines and
  ETL/ELT workflows supporting analytics, operational reporting, and AI/ML use
  cases.
• Implement best practice patterns for ingestion,
  transformation, modeling, and orchestration within a modern lakehouse
  environment (e.g., Databricks, Delta Lake, Azure Data Lake).
• Develop highperformance
  data models and curated datasets with strong attention to quality, usability,
  and interoperability; create reusable engineering components and automation.
• Collaborate with the Architecture Team, the Data
  Platform Lead, and federated IT teams to optimize storage, compute, and
  architectural patterns for performance and costefficiency.
• Build model-ready data sets and feature
  pipelines to support AI/ ML use cases; serve as a technical coordination point
  supporting business units' AI-related infrastructure needs.
• Collaborate with data scientists and AI Working
  Group to operationalize models responsibly and maintain ongoing monitoring
  signals.

Governance, Quality & Compliance

• Embed data governance, metadata standards,
  lineage tracking, and quality controls directly into engineering workflows;
  ensure technical implementation and alignment within engineering workflows.
• Work with the Data Governance Lead and business
  stakeholders to operationalize stewardship, classification, validation,
  retention, and access standards.
• Implement privacybydesign and securitybydesign
  principles, ensuring compliance with internal policies and regulatory
  obligations.
• Maintain documentation for pipelines, datasets,
  and transformations to support transparency and audit requirements.

Platform Reliability, Observability & Optimization

• Monitor and troubleshoot pipeline failures,
  performance bottlenecks, data anomalies, and platformlevel issues.
• Implement observability tooling, alerts,
  logging, and dashboards to ensure endtoend reliability.
• Support cost governance by optimizing compute
  resources, refining job schedules, and advising on efficient architecture.
• Collaborate with the Data Platform Lead on
  scaling, configuration management, CI/CD pipelines, and environment management.
• Collaborate with business units to understand
  data needs, translate them into engineering requirements, and deliver
  fit-for-purpose data solutions; share and apply best practices and emerging
  technologies within assigned initiatives.
• Work with IT Security and Legal/ Compliance to
  ensure platform and datasets meet risk and regulatory standards.

Staff Management

• Lead, mentor, and provide management oversight
  for staff.
• Responsible for setting objectives, evaluating
  employee performance, and fostering a collaborative team environment.
• Responsible for developing staff knowledge and
  skills to support career development.

May include other responsibilities as assigned

REQUIREMENTS:

1. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field preferred or equivalent work experience and HS diploma/equivalent education required.
2. 5+ years of experience in data engineering within cloud environments
3. Experience in people management preferred.
4. Demonstrated hands-on experience with modern data platforms (Databricks preferred).
5. Proficiency in Python, SQL, and data
   transformation frameworks.
6. Experience designing and operationalizing
   ETL/ELT pipelines, orchestration workflows (Airflow, Databricks Workflows), and
   CI/CD processes.
7. Solid understanding of data modeling,
   structured/unstructured data patterns, and schema design.
8. Experience implementing governance and quality
   controls: metadata, lineage, validation, stewardship workflows.
9. Working knowledge of cloud architecture, IAM,
   networking, and security best practices.
10. Demonstrated ability to collaborate across
    technical and business teams.
11. Exposure to AI/ML engineering concepts, feature
    stores, model monitoring, or MLOps patterns.
12. Experience with infrastructureascode
    (Terraform, CloudFormation) or DevOps tooling.

The American Medical Association is located at 330 N. Wabash Avenue, Chicago, IL 60611 and is convenient to all public transportation in Chicago.