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Senior Data Engineer

4 weeks ago

Minneapolis, Minnesota, United States Fairview Health Services Full time
Job Summary

The Senior Data Engineer will lead the implementation, maintenance, and architecture of the M Health Fairview data environment. This role involves planning, designing, and deploying enterprise data strategies by analyzing and translating business needs into a long-term data model solution that reduces redundancies, streamlines data movements, and improves enterprise information management.

The Senior Data Engineer will also support the day-to-day operations of the data environment by monitoring data pipelines and troubleshooting any errors or performance issues that may occur, ensuring complete and timely availability of data. They will assist with managing access to data to ensure its security and compliance with HIPAA guidelines.

This role works independently to design, document, and develop solutions that deliver data and analytics to clinical and operational senior and executive leaders. The Senior Data Engineer will operate under an SDLC model, leveraging best practices in development, testing, and deployment of data and analytics solutions.

Responsibilities:

  • Implement effective large, complex database and/or platform solutions and models to store and retrieve data based on architecture design.
  • Define and implement data strategies, policies, controls to ensure accurate, complete, secure, trusted, reliable enterprise data.
  • Apply leadership skills with IT, business owners, and end users to define and document business, technical, and operational requirements.
  • Champion initiatives to help the organization understand and improve data consistency, quality, and flows.
  • Captures, cleanses, and transforms data to provide insight and actionable recommendations independently.
  • Assess database implementation procedures to ensure they comply with internal and external regulations.
  • Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
  • Recommend solutions to improve new and existing database systems and data pipelines.
  • Introduce and advocate for industry best practices of modern data warehouse such as customer-centric, adaptable, automated, elastic, governed, secure, etc.
  • Prepare accurate database design and structure documentation for management and executive teams.
  • Creates and leads independently enterprise level initiatives to produce written narrative summaries that outline project purpose, methodology, summary of findings, trends of interest, and opportunities for consideration.
  • Educate team members on standards and best practices through training and individual support.

Qualifications:

  • Bachelor's Degree or certification of Associate Degree in related field, equivalent combination of education and work experience.
  • 5+ years of experience in data analysis and/or data architecture.
  • 5+ years of experience with various data models; Kimball, Inmon, and vaults.
  • 5+ years of experience with SQL(PL/SQL or T-SQL).
  • 5+ years of experience in application development, data analysis, data consolidation, or data management / governance.
  • 5+ years of experience with database principles, processes, technologies along with working knowledge of Extract, Transform and Load (ETL) principles, processes, technologies and tools.
  • Experience implementing and maintaining continuous integration/continuous delivery (CI/CD) processes.
  • Experience in multiple data modeling methodologies such as Data Vault and Kimball Dimensional Modeling for both structured and unstructured data.
  • Ability to read and write complex queries joining multiple data sets.
  • Ability to write and troubleshoot stored procedures.
  • Ability to analyze SQL execution plans and create appropriate indexes on tables with poorly performing queries.
  • Excellent technical and interpersonal communication skills.
  • Strong organizational and time management skills.
  • Ability to effectively manage and organize multiple projects and responsibilities.
  • Strong quantitative and analysis skills.
  • Ability to think creatively and work collaboratively to address problems.
  • Advanced knowledge of Azure platform/data tools such as Azure Data Lake, Azure Data Factory, Azure Synapse, Power BI, DevOps, Databricks, and other associated technologies.
  • Advanced knowledge of Amazon Web Service tools such as Redshift, BigQuery, Looker, and other associated technologies.
  • Knowledge of or experience with data quality tools and data governance tools.