Swoop and MyHealthTeam, a Swoop company, transform the healthcare journey for millions of patients nationwide with innovative solutions. We’re committed to building an inclusive space where employees are valued for their unique perspectives and experiences.

Swoop is a leading provider of AI-driven, precision healthcare omnichannel solutions, focused on protecting consumer privacy while improving patient outcomes. By combining best-in-class audience targeting, 100% MLR-approved conversational AI agents, and now — through the acquisition of MyHealthTeam — the largest opted-in social network of patients facing chronic conditions, Swoop delivers measurable Rx lift, deeper patient engagement, and trusted provider interactions across the care journey.

With over 4 million members across 60+ condition-specific social networks, MyHealthTeam  is  the fastest-growing social platform in chronic health. We believe that when someone is diagnosed with a condition like MS, lupus, breast cancer, or diabetes, they should easily find support, trusted information, and community. We’re working toward a future where social support is prescribed alongside clinical care.

About the role

We’re looking for a mid- to senior-level Data Engineer to join our growing Data Team, reporting to the Senior Director of Data Engineering. You’ll design and maintain data pipelines, models, and infrastructure that power analytics, insights, and personalization for millions. Our modern stack includes AWS, Redshift, Databricks, Airflow, and Spark, with Python and SQL as core languages. This is a key role in delivering scalable, reliable data solutions across the organization.

What you'll do

• Develop scalable, cloud-based data pipelines integrated with data warehouses like Redshift or Snowflake.
• Orchestrate data workflows using tools like Airflow, Prefect, and Dagster to ensure reliable pipeline execution.
• Design, optimize, and maintain data models, SQL queries, and Spark-based data processing workflows.
• Work across data lakehouse and warehouse systems to deliver clean, reliable, and analytics-ready data.
• Ensure high standards of data quality, governance, and security.
• Collaborate cross-functionally with the Data Analytics, Product, and Marketing teams to gather and improve data to enable actionable insights.
• Monitor and optimize performance of data systems and troubleshoot issues as needed.
• This is an individual contributor role reporting to the Senior Director of Data Engineering.

Qualifications

• Minimum eight (8) years of experience in data engineering, with a strong focus on ETL/ELT pipelines, cloud platforms, and data modeling
• Hands-on experience designing and managing scalable, cloud-native data pipelines using AWS services such as S3, Redshift, Glue, and Lambda
• Strong background in utilizing Databricks and Apache Spark to perform large-scale data transformation, processing, and analytics
• Strong programming skills in Python and SQL
• Solid understanding of data modeling, warehousing, and pipeline performance tuning
• Experience delivering production-ready ETL/ELT pipelines
• Infrastructure-as-code experience (Terraform, CloudFormation) desired
• Familiarity with containerization (Docker, Kubernetes) desired
• Analytical, detail-oriented, and adaptable with a strong sense of ownership
• Skilled in cross-functional collaboration, stakeholder alignment, and clear communication