Senior Engineering Manager (Data Engineering)

Join Omada Health as a Senior Engineering Manager (Data Engineering). In this role, you will lead a team responsible for designing, building, and operating scalable data pipelines that serve as the foundation for business intelligence, machine learning features, product analytics, operational reporting, experimentation, and advanced analytics. You will partner closely with various teams to define the technical strategy, execution roadmap, and operating model for Data Engineering. This position requires a strong balance of organizational leadership and technical depth, as you will build high-performing engineering teams, drive platform strategy, and deliver reliable, scalable, and governed data capabilities.

• Establish and execute a strategic roadmap for Omada's Data Engineering platform, leading the delivery of scalable, reliable, and governed data products.
• Lead, develop, and grow a high-performing Data Engineering organization through hiring, coaching, mentoring, and career development.
• Partner closely with Data Architects, Product Managers, Analytics, Data Science, Governance, and Software Engineering teams to define the technical strategy, execution roadmap, and operating model for Data Engineering.
• Proven ability to build, mentor, and scale high-performing engineering organizations
• Strong experience partnering with Product, Analytics, Data Science, and executive stakeholders
• 10+ years of experience building and operating large-scale data platforms, analytics systems, or software platforms
• Deep experience designing and operating modern cloud-based analytics platforms, including data warehouses, lakehouses, ELT/ETL pipelines, and data processing systems
• Familiarity with AI and machine learning data workflows is a plus
• 5+ years of experience leading Data Engineering teams, with experience managing managers or multiple teams preferred
• Experience implementing data quality, observability, governance, metadata, lineage, and access control capabilities
• Strong understanding of data modeling, analytics architecture, semantic layers, and scalable data product design
• Experience modernizing enterprise data platforms and driving adoption of modern data engineering practices
• Demonstrated success defining technical strategy, driving execution, and delivering complex cross-functional initiatives
• Experience with modern data technologies such as Databricks, Spark, Airflow, Kafka, Redshift, Snowflake, Python, SQL, Graph DB and AWS
• Education: Bachelor’s degree in Computer Science or a similar discipline preferred
• Passion for mentoring engineers and developing future technical leaders
• Ability to balance immediate business needs with long-term platform investments
• Comfortable operating in ambiguous environments and creating clarity, alignment, and execution
• Strong understanding of distributed data systems, cloud-native architectures, and software engineering practices
• Ability to influence technical direction across multiple engineering teams and organizational boundaries
• Experience with CI/CD, infrastructure automation, testing frameworks, monitoring, and performance optimization
• Exceptional leadership, communication, and stakeholder management skills
• Familiarity with modern data governance platforms such as Unity Catalog, Collibra, or OpenMetadata is a plus
• Technologies we use: Ruby on Rails, Redshift, Athena, Postgres, SQL, Python, Apache Airflow, Appflow, S3, SNS, SQS, Kafka, Docker, Kubernetes, AWS infrastructure, Lambda, Serverless, Tableau, Datadog, GitLabCI, Cursor, OpenMetadata, Databricks
• Experience building data pipelines for Healthcare or highly governed industries is a big plus