Senior Software Engineer, Data Engineering

Senior Software Engineer, Data Engineering

Remote, USA

Omada Health is on a mission to inspire and engage people in lifelong health, one step at a time.

Job overview: We are dedicated to leveraging data to drive strategic decision‑making and operational efficiency. Our team is passionate about harnessing the power of data to solve complex problems and deliver impactful insights.

We are seeking a highly skilled and motivated Data Engineer to join our team. The ideal candidate will be responsible for designing, building, and maintaining robust data architectures and engineering data models and pipelines. This role will play a critical part in ensuring the integrity, scalability, and performance of our data processing and products.

Key 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.

How you can make an impact:

• You’ll evaluate, benchmark, and improve the scalability, robustness, and performance of our data platform and applications.
• You'll make significant contributions to the architecture and design of our data processing platform.
• You’ll implement scalable, fault tolerant, and accurate ETLs frameworks.
• You’ll gather and process raw data at scale from diverse sources.
• You’ll collaborate with product management, data scientists, analysts, and other engineers on technical vision, design, and planning.
• You’ll implement and maintain a high level of data quality monitoring in our analytics & ML ecosystem.
• You’ll train and collaborate with teammates effectively in data engineering best practices.
• You will be responsible for leading, documenting, and collaborating across teams for technical projects.

You will love this job if you:

• You are passionate about building data‑driven systems to enable Data Scientists, Data Analysts and AI/ML Engineers.
• You want to make a difference to empower digital healthcare through data‑driven decision making.
• You would like to learn how to build scalable, performant and reliable data pipelines.

What you need for this role:

• 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.
• Fami…