As a Senior Data Engineer, you will build personalized & data driven healthcare data products and pipelines that power our Powered by League platform and provide valuable insights on its performance. Your role will be a combination of Data, Software, and DevOps Engineering. You will help architect, improve on and support a highly available, secure and governed data platform. 

In this role, you will work as part of a multi-disciplinary data platform team to establish and evangelize a data driven culture via various data pipelines (real time and batch), as well as design and build critical user-facing services. This team will not only work closely with the product and backend teams but will also support non-engineering functions like Marketing and Business Strategy.

To thrive in this role, you are someone who works well in cross-functional teams, enjoys collaborating, and loves taking ownership of a problem. Furthermore, you understand the business impact of your work and enjoy measuring and presenting it. You enjoy working with product management and other stakeholders to find the best solution to the problem at hand, iterate over it and can balance technical complexity with delivering customer value.

Our platform and applications run on Google Cloud, and the Data Platform team manages its own infrastructure in a way that aims for robust, scalable, and efficient deployments through Terraform. You will have an opportunity to experiment with new frameworks and paradigms, and freedom to put cutting-edge tech in production to shape the future of digital health!

• Design, build, and optimize scalable stream and batch pipelines using a variety of distributed computing platforms and tools such as: Airflow/Cloud Composer and Apache Beam/Dataflow
• Design, build, and optimize microservices that serve critical backend capabilities using services such as Cloud Functions and Cloud Run
• Design, build, and optimize the Data Platform’s DevOps process, including infrastructure as code, CI/CD, and other software development processes using tools such as Terraform, Github Actions, Cloud Build
• Drive architectural choices and data platform tools.
• Guide and mentor data engineers while teaching/encouraging software best practice guidelines.
• Translate business needs into data and analytics requirements, with attention to detail.
• Analyze, tune, troubleshoot and support the data infrastructure ensuring the quality, performance, integrity, and security of data.
• Use sound agile development practices (testing and code reviewing, etc.) to develop and deliver data products.

• Minimum 5 years experience in data engineering.
• Ability to articulate pros and cons of technical decisions and influence stakeholders.
• Experience in a cloud Data Stack  - preferably GCP.
• Experience in coding in python and SQL, bonus for experience in GoLang
• Experience in orchestration tools like Airflow.
• Experience in developing real time and batch pipelines. 
• Experience in software development of critical microservices with focus on reliability and optimization
• Experience in implementing deployments, error handling and monitoring for scalable pipelines.
• Experience in performing root cause analysis of production issues, performance tuning and optimization.

Nice to have:

• Experience in healthcare datasets like EMR and Claims and interoperability standards like FHIR.
• Experience in supporting reporting tools as a platform eg- Looker, Tableau.
• Experience in data modeling, data governance and data discovery tools.

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