SENIOR DATA ENGINEER
· Create data architecture, pipelines, and analytical solutions to meet software and data science requirements for various PG Healthcare Products
· Build out infrastructure, create custom solutions, and leverage industry tools to accomplish project and ad-hoc objectives
· Identify and implement improvements for data reliability, efficiency and quality
· Identify, evaluate, select, and prove out new technologies and toolsets
· Create and execute Proofs of Concept and Proofs of Technology
Building Data Pipelines
· Build, extend, or leverage solutions to acquire, transform, and store data for use in analytical context
· Analyze and improve performance, scalability, and fault tolerance
Cloud Compute and Data Lake
· Use large data sets to solve business problems
· Leverage analytical skills with unstructured or minimally structured datasets
· Build solutions using massively parallel processing cloud technologies (i.e., Databricks)
· Use appropriate languages to assemble and analyze datasets
Data Storage Design
· Collaborate with software development, business teams, and data scientists to establish data storage, pipeline, and structure requirements
· Identify and plan for data storage performance requirements
Application Interface and Data Storage Implementation
· Collaborate with software development, business teams, and data scientists to create and execute implementations
· Identify impact of implementation on other applications and databases
· Lead and mentor data engineers on data projects
Master Data Management and Data Governance
· Assist team to build and evolve Trusted Record systems to manage entities across the enterprise
· Design, implement, and evolve solutions around person identity management
Data Wrangling
· Identify patterns in data
· Discover opportunities to automate and optimize tasks
· Perform root cause analysis and remediate data issues
Mentorship
· Identify areas of development and need
· Provide targeted training and exploration for team members
· Train and mentor data engineers on standards and best practices
· Demonstrated knowledge of Azure data technologies (Databricks, ADF, Stream Analytics, ADLS, Synapse), on-premises Microsoft tools (SQL DB and SSIS), and familiar with AWS data technologies
· Fluent in SQL and Python, and familiar with PowerShell, and APIs
· Significant experience with analytical solutions in relational databases such as MS SQL Server, Oracle, and DB2 as well as experience with NoSQL databases and solutions such as data lakes, document-oriented databases, and graph databases
· Skill in data modeling and experience (ex. Tools like ER/Studio, Erwin, or other)
· Candidate will have great communication skills both verbal and writing at a team and leadership level
· Preferred experience with major EHR and data-exchange technologies (i.e., HL7, FHIR)
· Preferred experience with person identity management and entity resolution processing.
· Preferred experience in Data Science – statistical analysis and machine learning
· Minimum of 5 years Information Management experience in an enterprise environment