Duties:The analytics engineer acts as a bridge between a data engineer and a data analyst. This positionis primarily responsible for modeling raw data sets into curated, reusable, trusted data sets whichpower analytics across the enterprise. These data sets will serve as the single source of truth fordata and enable self-service analytics. In addition to the development of data models, this role isresponsible for maintaining data quality within these data sets via the use of monitoring, testing,and automation. An additional component of the role is to improve the effectiveness of dataanalysts and data scientists. This maybe via providing technical expertise in query development,extending data models via the addition of new metrics, and/or consulting on software developmentpractices. The Analytics Engineer owns the entire workflow of data associated with their domain;data pipeline development, ELT performance, timely loading of data sets, and maintenance.This role will work within various business units and partner with data analysts and data scientiststo obtain a deep understanding of operational data and develop scalable data products whichempower data-driven decision making across the enterprise.1. Collaborate with business subject matter experts, data analysts, and data scientists tounderstand/identify the opportunities to develop well-defined, integrated, re-usable datasets which power analytics.2. Codify reusable data access patterns to speed up time to insights.3. Perform Logical and Physical data modeling with an agile mindset.4. Build automated, scalable, test-driven ELT pipelines.5. Utilize software development practices such as version control via Git, CI/CD, and releasemanagement6. Build data products using various visualization, BI tools and data science tools.7. Collaborate with Data Engineers, DevOps engineers and architects on improvementopportunities for DataOps tools and frameworks.8. Implement data quality frameworks and data quality checks.9. Help define analytical product roadmap to drive the business goals and superior qualityoutcomes.10. Work with Data Scientists, Statisticians and Machine learning engineers toimplement/scale advanced algorithms to solve health care, operational and qualitychallenges.11. Work independently and effectively manage ones time across multiple priorities andprojects.12. Make recommendations about platform adoption, including technology integrations,application servers, libraries, and frameworks.13. Participate in a shared production on-call support model.14. Be a critical part of a scrum team in an agile environment, ensuring the teamsuccessfully meets its deliverables each sprint.Skills:Prior experience in working with EPIC/CLARITY datasets are preferred.Strong SQL, Data Modeling and Data Warehousing fundamentals.Experience with data integration tools: DBT (must have), Informatica PowerCenter, MS Integration Services etc.Experience working with Qlik Sense (must have)Experience working with relation databases (Snowflake experience is preferred)Experience with software development practices; version control (github), code review, CI/CDPrior experience in working with EPIC/CLARITY datasets are preferred.Good hands-on experience with Linux (RHEL/Debian) operating systemAbility to code with other scripting languages such as Python, Bash, groovy etc.,Experience utilizing Agile methodology for development