Children's Hospital of Philadelphia-posted 16 days ago
Full-time • Mid Level
Philadelphia, PA
5,001-10,000 employees
Hospitals

The Analytics Engineer acts as a bridge between a data engineer and a data analyst. This position is primarily responsible for modeling raw data sets into curated, reusable, trusted data sets which power analytics across the enterprise. These data sets will serve as the single source of truth for data and enable self-service analytics. In addition to the development of data models, this role is responsible 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 data analysts 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 development practices. The Analytics Engineer owns the entire workflow of data associated with their domain; data pipeline development and performance management, timely loading of data sets, and maintenance. This role will work within various business units and partner with data analysts and data scientists to obtain a deep understanding of operational data and develop scalable data products which empower data-driven decision making across the enterprise. The Analytics Engineer must be comfortable with mentoring and leading team development and skill development initiatives.

  • Collaborate with business subject matter experts, data analysts, and data scientists to understand/identify the opportunities to develop well-defined, integrated, re-usable data sets which power analytics.
  • Codify reusable data access patterns to speed up time to insights.
  • Perform logical and physical data modeling with an agile mindset.
  • Build automated, scalable, test-driven data transformation pipelines.
  • Utilize software development practices such as version control via git, CI/CD, and release management
  • Build data products using various visualization, BI tools and data science tools.
  • Collaborate with Data Engineers, DevOps engineers and Architects on improvement opportunities for DataOps tools and frameworks.
  • Implement data quality frameworks and data quality checks.
  • Help define analytical product roadmaps to drive the business goals and superior quality outcomes.
  • Work with Data Scientists, Statisticians and Machine Learning Engineers to implement/scale advanced algorithms to solve health care, operational and quality challenges.
  • Work independently and effectively manage time and resources across multiple priorities and projects.
  • Make recommendations about platform adoption, including technology integrations, application servers, libraries, and frameworks.
  • Participate in a shared production on-call support model.
  • Be a critical part of a scrum team in an agile environment, ensuring the team successfully meets its deliverables each sprint.
  • Train and mentor team members
  • Develop a "trusted advisor" reputation through expertise in data and business processes.
  • Bachelor's Degree Computer Science, Computer/Software Engineering, Information Technology or related fields - Required
  • At least six (6) years experience working in Data and analytics landscape - Required
  • Strong SQL, Data Modeling and Data Warehousing fundamentals.
  • Experience with data integration tools such as dbt and Kinesis.
  • Experience of data integration tools: DBT, Informatica, MS Integration Services etc.
  • Experience with the Snowflake data platform
  • Experience working with at least one of the Business Intelligence platforms (Business Objects, Cognos, Microstrategy etc.,) or visualization tools such as Qlik, Tableau, Power BI etc.,
  • Hands-on experience with Linux (RHEL/Debian) operating system
  • Knowledge of version control systems such as git.
  • Ability to code with scripting languages such as python, bash, groovy etc.,
  • Experience building and using APIs
  • Experience utilizing Agile methodology for development
  • Master's Degree Computer Science, Informatics, Information Systems or another quantitative field -Preferred
  • At least eight (8) years of experience working in Data and analytics landscape - Preferred
  • At least two (2) years of experience working with at least one of the public cloud platforms such AWS/Azure/GCP - Preferred
  • Experience with healthcare finance - Preferred
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