Data Engineer, Crossover Health

• The ideal candidate will have experience with both clinical healthcare data as well as healthcare claims data
• Bachelors in Computer Science, related degree, or equivalent professional experience
• 6+ years relevant work experience within a complex, dynamic environment, with preference for experience with clinical healthcare data
• 6+ years architecting , implementing, and supporting data infrastructure and data warehousing
• Experience building and operating highly available, distributed systems of extraction, ingestion, and processing of large data sets across a variety of applications (OLTP, OLAP and DSS)
• Experience developing and designing a Snowflake environment
• Experience with data migration tools and deploying cloudbase solutions
• Strong knowledge of advanced SQL (DML & DDL), including Stored Procedures, Indexes, user defined functions, windows functions, correlated subqueries and CTE's, and related data query and management technology
• Strong coding ability in Python, R, and Shell Scripting to build and deploy Pipelines
• Working knowledge of Git, or similar collaborative code management software
• Experience with data integration tools such as Matillion, FiveTran, Airflow, or similar ETL/ELT/Orchestration tools
• Experience with Snowflake’s data platform

Desirable

• Crossover’s Sr. Data Engineer is responsible for managing and developing data sources for analytics at scale. This is a critical role for supporting Crossover’s growing analytics team, and serves as the connection between Crossover’s Information Technology team, Data Science team, and data infrastructure vendors
• In this role, the successful candidate will build out new data sources within the enterprise data warehouse, guide data modeling efforts for new and existing projects, and manage data ingress and egress between Crossover teams, clients, partners, and vendors
• Develop and maintain data sources within Crossover’s enterprise data warehouse (inclusive of our current vendor and/or future data infrastructure)
• Lead the development of a comprehensive data strategy and roadmap, including recommendations for data architecture, data storage, data integration, data quality, and data models
• Design and build data models to clean and transform datasets for use by Crossover’s Data Science team
• Manage ETL, ELT, and reverse-ETL design and development initiatives including data analysis, source-target mapping, data profiling, change data capture, QA testing, and performance tuning to guarantee quality and repeatability of data model results
• Create and maintain data model standards, including MDM (Master Data Management) and codebase standardization
• Build Enterprise Workload migration strategies into Snowflake using industry standard methodologies
• Automate and deploy as well as build CI/CD pipelines to support cloud based workload
• Design, deliver cloud native, hybrid, and multi-cloud Workloads
• Invest in documentation, including all system design, architecture and ongoing changes
• Design and support production job schedules, including alerting, monitoring, break fixes, and performance tuning
• Build solutions that are automated, scalable, and sustainable while minimizing defects and technical debt
• Assist stakeholders including analytics, design, product, and executive teams with data-related technical issues
• Ability to work independently with little instruction or direct oversight
• Perform other duties as assigned