Senior Engineering Manager, Data Engineering
New
O
Omada HealthHealthcare
Remote, USAFull-TimeManager
SalaryCalifornia, New York State and Washington State Base Compensation Ranges: $202,400 - $253,000*, Colorado Base Compensation Ranges: $193,600 - $242,000*
Apply NowOpens the employer's application page
Job Details
- 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
- Required Skills
- PythonSQLApache AirflowKafkaSnowflakeData engineeringSparkDatabricks
Requirements
- 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.
- 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.
- 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, and AWS.
- Exceptional leadership, communication, and stakeholder management skills.
- Bachelor’s degree in Computer Science or a similar discipline preferred.
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.
- Partner with Product, Analytics, Data Science, Architecture, Governance, and Engineering leaders to define priorities and accelerate data-driven decision making.
- Establish engineering excellence through improved data quality, reliability, observability, security, and platform performance.
View Full Description & ApplyYou'll be redirected to the employer's site
