Role overview

Senior Software Engineer, Data Engineering

Requirements and responsibilities

Readable role content extracted into sections for faster review.

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 Scientist, 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.

About you: Experience:

  • 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.

Technical Skills:

  • 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, Iceberg or Delta Lake, Spark, or Kafka)
  • Software engineering mindset and an ability to write elegant, maintainable code while following engineering best practices

Bonus Points for:

  • Experience with NoSQL databases (e.g., document and graph databases)

Bonus Points for:

  • Experience building data infrastructure, frameworks and automation is a big plus.
  • Experience using Generative AI tools or technologies to improve engineering workflows, automation, analytics, or data platform capabilities.

Benefits:

  • Competitive salary with generous annual cash bonus
  • Equity grants
  • Remote first work from home culture
  • Flexible Time Off to help you rest, recharge, and connect with loved ones
  • Generous parental leave
  • Health, dental, and vision insurance (and above market employer contributions)
  • 401k retirement savings plan
  • Lifestyle Spending Account (LSA)
  • Mental Health Support Solutions
  • ...and more!

Benefits:

  • Cultivate Trust. We listen closely and we operate with kindness. We provide respectful and candid feedback to each other.
  • Seek Context. We ask to understand and we build connections. We do our research up front to move faster down the road.
  • Act Boldly. We innovate daily to solve problems, improve processes, and find new opportunities for our members and customers.
  • Deliver Results. We reward impact above output. We set a high bar, we’re not afraid to fail, and we take pride in our work.
  • Succeed Together. We prioritize Omada’s progress above team or individual. We have fun as we get stuff done, and we celebrate together.
  • Remember Why We’re Here. We push through the challenges of changing health care because we know the destination is worth it.
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FocusData EngineeringRole area
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