Senior Software Engineer - Data Engineering

1w1 week ago

Omada Health

US · Full-time · $171,600 – $224,300

About this role

Omada Health is on a mission to inspire and engage people in lifelong health, one step at a time. We are dedicated to leveraging data to drive strategic decision-making and operational efficiency. Our team is passionate about harnessing data to solve complex problems and deliver impactful insights.

We seek a highly skilled Data Engineer to design, build, and maintain robust data architectures, engineering models, and pipelines. This role ensures the integrity, scalability, and performance of data processing and products. You will play a critical part in creating efficient data solutions.

Partner closely with data scientists, analysts, and stakeholders to understand requirements and deliver tailored solutions. Train and collaborate with teammates in data engineering best practices. Provide technical influence, recommend policy changes, and resolve complex problems.

Evaluate, benchmark, and improve the scalability, robustness, and performance of our data platform. Make significant contributions to architecture and design of data processing. Implement scalable, fault-tolerant ETL frameworks and maintain high data quality monitoring.

Requirements

5+ years of experience building, maintaining, and orchestrating scalable data pipelines
3+ years of experience as a data engineer developing or maintaining data systems
Experience designing scalable data architectures
Expertise in data modeling for business intelligence and analytics
Proficiency in ETL pipeline engineering and optimization
Knowledge of data integration from diverse sources
Skills in data quality assurance and governance
Ability to provide technical leadership and resolve complex data problems

Responsibilities

Design, develop, and implement scalable, secure, and efficient data solutions
Create and maintain logical and physical data models to support analytics and reporting
Design, build, and optimize ETL processes and data pipelines for efficient data flow
Integrate diverse data sources including APIs, databases, and third-party data
Monitor and optimize performance of data systems for low latency and high throughput
Implement data quality checks, validation processes, and governance frameworks
Collaborate with data scientists, analysts, and stakeholders on data requirements
Monitor and manage production environment to deliver data within defined SLAs