Senior Engineering Manager, Data Engineering
at Omada Health
- Seniority
- Lead Manager
- Work model
- Remote
- Location
- Remote, USA
- Posted
- 15d ago
pythonrubyrailsrestpostgreskafkaawskubernetesdockerserverlesslambdasnowflake
at Omada Health
<p>Omada Health is on a mission to bend the curve of chronic disease.</p> <p><strong>Job overview: </strong></p> <p>Our Data Engineering team builds and operates the data platform and curated data products that power analytics, reporting, experimentation, and AI-driven insights across Product, Clinical, Commercial, Finance, and Operations. We are looking for an experienced <strong>Senior Engineering Manager, Data Engineering</strong> to lead our data engineering organization and help shape the future of Omada's enterprise data platform.</p> <p>As a Senior Engineering Manager, you will lead a team responsible for designing, building, and operating scalable data pipelines that serve as the trusted foundation for business intelligence, machine learning features, product analytics, operational reporting, experimentation, and advanced analytics.</p> <p>You will 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.</p> <p>This role requires a strong balance of organizational leadership and technical depth. You will build high-performing engineering teams, drive platform strategy, and deliver reliable, scalable, and governed data capabilities that enable data-driven decision making across Omada.</p> <p><strong>Key Responsibilities:</strong></p> <ul> <li>Establish and execute a strategic roadmap for Omada's Data Engineering platform.</li> <li>Lead the delivery of scalable, reliable, and governed data products that enable analytics, reporting, experimentation, and AI-driven insights.</li> <li>Deliver trusted, reusable production datasets that power Applied Data Science, Product, Clinical, Commercial, Finance, Operations, and Executive analytics.</li> <li>Lead, develop and grow a high-performing Data Engineering organization through hiring, coaching, mentoring, and career development.</li> <li>Foster a culture of technical excellence, collaboration, accountability, and continuous learning.</li> <li>Empower teams to deliver high-impact solutions while maintaining a strong focus on quality and operational excellence.</li> <li>Partner with Product, Analytics, Data Science, Architecture, Governance, and Engineering leaders to define priorities and accelerate data-driven decision making across Omada.</li> <li>Translate business needs into scalable platform capabilities and trusted data products.</li> <li>Build strong relationships across the organization to drive alignment, transparency, and execution.</li> <li>Establish engineering excellence through improved data quality, reliability, observability, security, and platform performance.</li> <li>Define and monitor engineering and operational metrics to continuously improve platform health, cost efficiency, and developer productivity.</li> <li>Guide adoption of Improved reliability, quality, governance, and usability of enterprise data products.</li> <li>Provide technical leadership for architecture, platform evolution, scalable technologies, reusable frameworks, and engineering standards across Data Engineering.</li> <li>Expand self-service analytics through trusted and reusable data capabilities.</li> <li>Influence long-term technology strategy while partnering with engineering leaders across Omada to build a world-class data platform.</li> </ul> <p><strong>About you: </strong></p> <p><strong>Experience:</strong></p> <ul> <li>10+ years of experience building and operating large-scale data platforms, analytics systems, or software platforms.</li> <li>5+ years of experience leading Data Engineering teams, with experience managing managers or multiple teams preferred.</li> <li>Proven ability to build, mentor, and scale high-performing engineering organizations.</li> <li>Demonstrated success defining technical strategy, driving execution, and delivering complex cross-functional initiatives.</li> <li>Strong experience partnering with Product, Analytics, Data Science, and executive stakeholders.</li> <li>Deep experience designing and operating modern cloud-based analytics platforms, including data warehouses, lakehouses, ELT/ETL pipelines, and data processing systems.</li> <li>Strong understanding of data modeling, analytics architecture, semantic layers, and scalable data product design.</li> <li>Experience implementing data quality, observability, governance, metadata, lineage, and access control capabilities.</li> <li>Experience modernizing enterprise data platforms and driving adoption of modern data engineering practices.</li> <li>Familiarity with AI and machine learning data workflows is a plus.</li> </ul> <p><strong>Technical Skills:</strong></p> <ul> <li>Strong understanding of distributed data systems, cloud-native architectures, and software engineering practices.</li> <li>Experience with modern data technologies such as Databricks, Spark, Airflow, Kafka, Redshift, Snowflake, Python, SQL, Graph DB and AWS.</li> <li>Experience with CI/CD, infrastructure automation, testing frameworks, monitoring, and performance optimization.</li> <li>Familiarity with modern data governance platforms such as Unity Catalog, Collibra, or OpenMetadata is a plus.</li> </ul> <p><strong>Communication Skills:</strong> </p> <ul> <li>Exceptional leadership, communication, and stakeholder management skills.</li> <li>Ability to influence technical direction across multiple engineering teams and organizational boundaries.</li> <li>Passion for mentoring engineers and developing future technical leaders.</li> <li>Ability to balance immediate business needs with long-term platform investments.</li> <li>Comfortable operating in ambiguous environments and creating clarity, alignment, and execution.</li> </ul> <p><strong>Education:</strong> Bachelor’s degree in Computer Science or a similar discipline preferred.</p> <p><strong>Technologies we use:</strong> Ruby on Rails, Redshift, Athena, Postgres, SQL, Py