Senior Software Engineer, Data Engineering

Omada Health is on a mission to inspire and engage people in lifelong health, one step at a time. They are seeking a highly skilled Data Engineer to design, build, and maintain robust data architectures and engineering data models and pipelines, ensuring data integrity, scalability, and performance.

Responsibilities:

• Data Architecture: Design, develop, and implement scalable, secure, and efficient data solutions that meet the needs of the organization
• Data Modeling: Create and maintain logical and physical data models to support business intelligence, analytics, and reporting requirements
• Pipeline Engineering: Design, build, and optimize ETL (Extract, Transform, Load) processes and data pipelines to ensure smooth and efficient data flow from various sources
• Data Integration: Integrate diverse data sources, including APIs, databases, and third-party data, into a unified data platform
• Performance Optimization: Monitor and optimize the performance of data systems and pipelines to ensure low latency and high throughput
• Data Quality and Governance: Implement data quality checks, validation processes, and governance frameworks to ensure the accuracy and reliability of data
• Collaboration: Partner closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions that meet their needs
• Documentation: Maintain comprehensive documentation of data architectures, models, and pipelines for ongoing maintenance and knowledge sharing
• Training: You'll train and collaborate with teammates effectively in data engineering best practices
• Technical Influence/Leadership: Recommends policy changes and establishes department-wide procedures. Uses extensive experience and knowledge to resolve complex problems
• Monitor and manage production environment to deliver data within defined SLAs

Requirements:

• 5+ years of experience building, maintaining, and orchestrating scalable data pipelines
• 3+ years of experience as a data engineer developing or maintaining integration with software such as Airflow or any Python-based data pipeline codebase
• Experience applying a variety of integration patterns for different use cases
• Experience in backend software development to contribute to distributed computing development and data technologies, with broad experience across systems, contexts, and ideas
• Experience implementing data pipelines and improving the performance of ETL processes and related SQL queries
• Experience in data modeling for OLTP and OLAP applications
• Experience with Cloud platforms such as Amazon AWS
• Familiarity with workflow management tools (Airflow preferred)
• Familiarity with cloud-based data warehouses (Amazon Redshift preferred)
• Exceptional Problem solving and analytical skills
• Experience working with sensitive data i.e. PHI / PII & security best practices
• Familiarity with data governance practices and principles
• Proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL)
• Proficiency in Analytical SQL (e.g. Analytics Queries, Distributed database queries) and experience working with massive parallel processing (MPP) databases (e.g., Redshift, BigQuery, Snowflake)
• Proficiency in programming languages such as Python, Java, or Scala
• Knowledge of data modeling techniques (3NF) and tools (e.g., ER/Studio, ERwin)
• Software Engineering Mindset: Apply best practices to write elegant, maintainable code and understand automated testing concepts
• Familiarity with business intelligence tools and environments
• Familiarity with big data technologies (e.g., Lambda, Hadoop, Spark)
• Software engineering mindset and an ability to write elegant, maintainable code while following engineering best practices
• Excellent communication and collaboration skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders
• Leading projects and tasks effectively with cross functional stakeholders minimal guidance
• Bachelor's degree in Computer Science or a similar discipline preferred
• Experience with big data technologies such as Hadoop, Spark, or Kafka
• Experience building internal frameworks or development productivity tools would be a big plus
• Experience building data infrastructure, frameworks and automation is a big plus
• Understanding automated testing concepts and ability to consistently apply those concepts