Senior Data Engineer

<div class="content-intro"><p>At Collective Health, we’re transforming how employers and their people engage with their health benefits by seamlessly integrating cutting-edge technology, compassionate service, and world-class user experience design.</p></div><p>We deliver a connected healthcare experience for over a quarter million members and 60+ companies across the nation who want the best for their employees. We've got a ton of interesting problems to solve around data pipeline design and implementation, data architecture and modeling, distributed systems, and more. If you're passionate about tackling hard problems while making a real difference in the world, we'd love to talk!</p> <h3><strong>What you'll do:&nbsp;</strong></h3> <ul> <li>Data Infrastructure Orchestration - Build and maintain cloud native infrastructure for Data Platform (AWS, Terraform)</li> <li>Data Pipelines - Create new pipelines and improve/maintain existing pipelines using Spark (Python, Pyspark, SQL)</li> <li>Data Modeling - Partner with analytic consumers to design logical and physical schemas, improve existing data models and build new ones</li> <li>Cross-functional Collaboration - Interface with Product, Engineering, Data Science, Analytics/BI, and Operations to understand their data needs, providing both consultative and data engineering solutions for consumers</li> <li>Build data expertise and own data quality across various business domains including healthcare claims and member experience</li> <li>Manage the Business Intelligence development lifecycle, from semantic model development and version control to user administration, ensuring high data quality and consistency from the pipeline through to the visualization layer.</li> <li>Enable fellow developers to “self-service” their data needs</li> <li>Leverage best in industry practices to build the next generation data ecosystem to collect, move, store and analyze data</li> </ul> <h3><strong>To be successful in this role, you'll need:</strong></h3> <ul> <li>BS degree in Computer Science or related technical field, or equivalent practical experience</li> <li>4+ years proven work experience as a data engineer, working with at least one programming language (e.g. Scala, Python/PySpark) plus SQL expertise</li> <li>4+ years experience with schema design, dimensional data modeling, and large-scale data warehousing architecture</li> <li>Expertise in building data pipelines through efficient ETL design, implementation and maintenance&nbsp;</li> <li>Background working with distributed data systems such as Spark, Presto, Hive, and Redshift. Experience with BI platform administration and/or schedulers/workflow management tools (e.g. Airflow)