As a Senior Software Engineer I at Aledade, we maintain, improve, and expand our data models and Databricks pipelines. We're looking for engineers who know that writing new code is not always the solution to a problem, but when technological changes are needed they create secure, maintainable, performant, correct, scalable, and stable solutions to the complex and unique challenges in our corner of the healthcare industry.
The Patient Domain Team is responsible for turning complex health care data into well-defined insights about our patients that describes who they are and how they interact with the health care system. We are responsible for telling our partner practices more about who their patients are and how to ensure they receive the care they need. We are also responsible for figuring out how to monitor and observe our models in action to ensure they are driving impact across the company.
Primary Duties:
- Develop and implement scalable and performant solutions.
- Partner, as a peer, with Engineering Managers, Product Managers, and stakeholders throughout Aledade to develop and execute technical roadmaps using Agile processes.
- Mentor and coach more junior engineers including thorough pull request reviews for other developers and be receptive to critical feedback on your own work.
Minimum Qualifications:
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BS/BTech (or higher) in Computer Science, Engineering or a related field.
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3+ years of experience working with SQL or other database querying language on large multi-table data sets.
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4+ years experience as an engineer building backend applications as part of a cross-functional team.
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2+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value.
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2+ years of experience coaching other engineers.
Preferred KSAs:
- 2+ years of extensive Data Engineering Experience particularly in DataBricks and any Data Warehouses like Snowflake, BigQuery, Redshift.
- 3+ years of working in backend languages like Python, Java, Node.js etc.
- Experience in designing, building and optimizing data pipelines and ETL processes.
- Proficiency in working with large datasets and knowledge of data storage technologies.
- Experience working with data ingestion systems and optimizing performance for handling large-scale data processing and analysis
- In-depth knowledge of database systems.
- Experience in performance monitoring and optimization of data systems and infrastructure.
- Experience building Data pipelines using Kafka or similar stack.
- Familiarity with database replication, sharding and other techniques for scalability and high availability of databases.
- Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.
- Familiarity building continuous integration and continuous deployment(CI/CD) pipelines.
- Familiarity with security and systems that handle sensitive data.