Omada Health - Senior Software Engineer, Data Engineering
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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 • Communication Skills: Excellent communication and collaboration skills, both written and verbal, with the ability to convey complex technical concepts to non-technical stakeholders. • Self-Directed: Leading projects and tasks effectively with cross functional stakeholders minimal guidance. You care about writing quality software and recognize that there are often many right answers. Ability to lead tasks and projects effectively. • Self-Directed: • Education: Bachelor’s degree in Computer Science or a similar discipline preferred. • Education: • Technologies we use: Ruby on Rails, Redshift, Athena, Postgres, SQL, Python, Apache Airflow, Appflow, S3, SNS, SQS, Kafka, Docker, Kubernetes, AWS infrastructure, Lambda, Serverless, Tableau, Bugsnag, Datadog, GitLabCI • Technologies we use: • 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
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 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.
Benefits
• Competitive salary with generous annual cash bonus • 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 • It takes a village to change health care. As we build together toward our mission, we strive to embody the following values in our day-to-day work. We hope these hold meaning for you as well as you consider Omada! • Cultivate Trust. We listen closely and we operate with kindness. We provide respectful and candid feedback to each other. • Cultivate Trust. • Seek Context. We ask to understand and we build connections. We do our research up front to move faster down the road. • Seek Context. • Act Boldly. We innovate daily to solve problems, improve processes, and find new opportunities for our members and customers. • Act Boldly. • 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. • Deliver Results. • Succeed Together. We prioritize Omada’s progress above team or individual. We have fun as we get stuff done, and we celebrate together. • Succeed Together. • Remember Why We’re Here. We push through the challenges of changing health care because we know the destination is worth it. • Omada is thrilled to share that we’ve been certified as a Great Place to Work! Please click here for more information. • We carefully hire the best talent we can find, which means actively seeking diversity of beliefs, backgrounds, education, and ways of thinking. We strive to build an inclusive culture where differences are celebrated and leveraged to inform better design and business decisions. Omada is proud to be an equal opportunity workplace and affirmative action employer. We are committed to equal opportunity regardless of race, color, religion, sex, gender identity, national origin, ancestry, citizenship, age, physical or mental disability, legally protected medical condition, family care status, military or veteran status, marital status, domestic partner status, sexual orientation, or any other basis protected by local, state, or federal laws. • Below is a summary of salary ranges for this role in the following geographies:
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