Senior Engineering Manager, Data Engineering
About the role
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 Senior Engineering Manager, Data Engineering to lead our data engineering organization and help shape the future of Omada's enterprise data platform.
Key Responsibilities
Establish and execute a strategic roadmap for Omada's Data Engineering platform.
Lead the delivery of scalable, reliable, and governed data products that enable analytics, reporting, experimentation, and AI-driven insights.
Deliver trusted, reusable production datasets that power Applied Data Science, Product, Clinical, Commercial, Finance, Operations, and Executive analytics.
Lead, develop and grow a high-performing Data Engineering organization through hiring, coaching, mentoring, and career development.
Foster a culture of technical excellence, collaboration, accountability, and continuous learning.
Empower teams to deliver high-impact solutions while maintaining a strong focus on quality and operational excellence.
Partner with Product, Analytics, Data Science, Architecture, Governance, and Engineering leaders to define priorities and accelerate data-driven decision making across Omada.
Translate business needs into scalable platform capabilities and trusted data products.
Partner with Product, Analytics, Data Science, and executive stakeholders to define priorities and accelerate data-driven decision making across Omada.
Build strong relationships across the organization to drive alignment, transparency, and execution.
Establish engineering excellence through improved data quality, reliability, observability, security, and platform performance.
Define and monitor engineering and operational metrics to continuously improve platform health, cost efficiency, and developer productivity.
Guide adoption of Improved reliability, quality, governance, and usability of enterprise data products.
Influence long-term technology strategy while partnering with engineering leaders across Omada to build a world-class data platform.
About you
Experience: 10+ years of experience building and operating large-scale data platforms, analytics systems, or software platforms. 5+ years of experience leading Data Engineering teams, with experience managing managers or multiple teams preferred. Proven ability to build, mentor, and scale high-performing engineering organizations. Demonstrated success defining technical strategy, driving execution, and delivering complex cross-functional initiatives. Strong experience partnering with Product, Analytics, Data Science, and executive stakeholders. Deep experience designing and operating modern cloud-based analytics platforms, including data warehouses, lakehouses, ELT/ETL pipelines, and data processing systems. Strong understanding of data modeling, analytics architecture, semantic layers, and scalable data product design. Experience implementing data quality, observability, governance, metadata, lineage, and access control capabilities. Experience modernizing enterprise data platforms and driving adoption of modern data engineering practices. Familiarity with AI and machine learning data workflows is a plus.
Technical Skills: Strong understanding of distributed data systems, cloud-native architectures, and software engineering practices. Experience with modern data technologies such as Databricks, Spark, Airflow, Kafka, Redshift, Snowflake, Python, SQL, Graph DB and AWS. Experience with CI/CD, infrastructure automation, testing frameworks, monitoring, and performance optimization. Familiarity with modern data governance platforms such as Unity Catalog, Collibra, or OpenMetadata is a plus. Communication Skills: Exceptional leadership, communication, and stakeholder management skills. Ability to influence technical direction across multiple engineering teams and organizational boundaries. 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. Education: Bachelor’s degree in Computer Science or a similar discipline preferred. 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. Bonus Points for: Experience building data pipelines for Healthcare or highly governed industries is a big plus.