Data Engineer

The American Lung Association is a nonprofit organization dedicated to improving lung health and preventing lung disease through research, education, and advocacy. The Data Engineer will design, build, maintain, and optimize governed data platforms, pipelines, models, and architectures supporting enterprise analytics, reporting, and AI/ML initiatives. The role partners with business stakeholders and governance teams to deliver scalable, reliable, and analytics-ready data solutions.

Responsibilities

• Design, build, and maintain reliable, scalable ETL/ELT pipelines to ingest data from diverse sources (APIs, SaaS platforms, databases, streaming sources, flat files)
• Develop and optimize batch and real-time data workflows using modern orchestration and transformation tools
• Ensure data quality, reliability, and observability through automated testing, monitoring, and alerting
• Partner with Data Team and business stakeholders to develop curated, analytics-ready data sources that enable self-service consumption
• Design conceptual, logical, and physical data models that support transactional, analytical, and reporting workloads
• Build and maintain semantic models and reusable datasets that make data intuitive and accessible for business users and downstream analytics tools
• Apply dimensional modeling (Kimball, data vault, or 3NF) approaches as appropriate to the use case
• Define and maintain data standards, naming conventions, and metadata documentation
• Collaborate with business stakeholders to translate domain knowledge into reusable, governed data structures
• Contribute to the enterprise data architecture roadmap, including Lakehouse, Warehouse, and streaming patterns
• Help evaluate and recommend tools, platforms, and design patterns that best fit enterprise needs
• Support the design of data integration, master data, and reference data strategies aligned with enterprise architecture principles
• Champion data governance, lineage, security, and compliance best practices in partnership with governance teams

Preferred

• Experience designing semantic layers or analytics-ready datasets to support self-service BI and reporting
• Familiarity with Data Vault 2.0, Data Mesh, or medallion architecture patterns
• Exposure to streaming technologies (e.g., Kafka, event-based ingestion, structured streaming)
• Experience working in regulated industries (healthcare, finance, insurance) and with PII/PHI data
• Relevant certifications in cloud data engineering, data management, or data modeling (e.g., CDMP, cloud-provider data engineering certifications)
• Interest in growing into a senior data engineering or data architecture role over time
• Semantic Layer Design
• Analytics-Ready Dataset Design
• Self-Service BI
• Data Vault 2.0
• Data Mesh
• Medallion Architecture
• Kafka
• Event-Based Ingestion
• Structured Streaming
• Regulated Industry Experience
• PII/PHI Data Handling
• Cloud Data Engineering
• Data Management
• CDMP Certification
• Cloud Data Engineering Certifications
• Career Growth Orientation

Benefits

• Hybrid: The position is located at the American Lung Association’s Chicago, Illinois office and will be a combination of in-person and virtual work.
• Paid Leave - 10 vacation days in the first year (15 days thereafter), 2 personal days and 15 sick days per year, as well as 12 company-paid holidays per year. We also offer Paid Parental Leave for eligible employees.
• Employees (and their eligible dependents) can enroll in our medical, dental, and vision plans, as well as voluntary plans for critical illness, accident, hospital indemnity, short-term disability and supplemental life/AD&D insurance.
• Employees will be enrolled in company-paid life/AD&D and long-term disability Insurance coverage.
• Eligible employees can participate in our 401(k) Defined Contribution Retirement Plan, which offers matching employer contributions (up to 4%) and year-end discretionary non-elective contributions.

Company

• Lung health nonprofit for disease prevention, research, education, and advocacy.
• Chicago, Illinois, USA
• http://www.lung.org/
• Founded in 1904
• 201-500 employees

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field, or an equivalent combination of education and experience
• 3+ years of hands-on data engineering experience building production data pipelines
• 1–2+ years of data modeling experience across OLTP and/or OLAP systems
• Strong proficiency in SQL and solid programming skills in Python or similar OOP languages
• Experience working with at least one cloud data platform (Azure, AWS, or GCP) and a modern warehouse or Lakehouse environment (Snowflake, MS Fabric, Databricks, etc.)
• Hands-on experience building data integrations to a data lake/warehouse environment, either via coding (SQL, etc..) or commercial ELT/ETL tools
• Working knowledge of dimensional modeling, star/snowflake schemas, and slowly changing dimensions
• Familiarity with semantic modeling concepts and developing curated data sources for analytics and BI consumption
• Understanding of data governance, security, lineage, and metadata management concepts
• Experience with CI/CD, Git, and version-controlled development for data workloads
• Strong communication skills — able to translate technical concepts for business stakeholders and the ability to translate business needs and logic to technical workflows
• Experience designing semantic layers or analytics-ready datasets to support self-service BI and reporting
• Familiarity with Data Vault 2.0, Data Mesh, or medallion architecture patterns
• Exposure to streaming technologies (e.g., Kafka, event-based ingestion, structured streaming)
• Experience working in regulated industries (healthcare, finance, insurance) and with PII/PHI data
• Relevant certifications in cloud data engineering, data management, or data modeling (e.g., CDMP, cloud-provider data engineering certifications)
• Interest in growing into a senior data engineering or data architecture role over time
• 3+ years of hands-on data engineering experience building production data pipelines.
• 1–2+ years of data modeling experience across OLTP and/or OLAP systems.

Required skills

• ETL/ELT Pipelines, SQL, Python, Data Modeling, Dimensional Modeling, Semantic Modeling, Data Governance, CI/CD, Git, AWS, Snowflake, Databricks

Experience

• 3+ years