Job Description :

The Data Analyst will work alongside the BI and engineering team to provide data related support, data investigation, research, data management and data reporting.  This role will be critical in reviewing business requirements, working across IT functions to research requests and partnering with engineering to ensure successful addition to our Analytical platform. The Data Analyst role will troubleshoot and investigate data anomalies and issues along with working directly with the data engineers to follow through and get the issues fixed. This person will also assist in building reporting and/or dashboard solutions to cover our data acquisition lifecycle. This is a great opportunity for someone who is interested in joining a lean, innovative group with the possibility of tremendous career development in data engineering and data science. 


  • Perform extensive data validation/quality assurance analysis within large datasets.
  • Build proactive data validation automation to catch data integrity issues.
  • Assist in building datasets by translating requirements into technical specification.  To include making data model modification recommendations.
  • Create, update and evolve our data model documentation.
  • Ability to organize and lead meetings with business and operational data owners.
  • Strong ability to troubleshoot and resolve data issues.
  • Ability to build tabular and/or visualization reports as needed.
  • Work closely with engineering and operations to document business processes.
  • Work independently and with team members to understand database structure and business processes.
  • Identify opportunities to improve data and business processes utilizing Python, R, or SQL.
  • Help form data management and governance processes within the data engineering team.


  • Education:  BS/BA in computer science, software engineering or mathematics.
  • Professional Experience:  Minimum two years of experience in design, development, administration, troubleshooting of analytical solutions.  
  • The ability to analyze, model and interpret data for analytics.
  • A strong belief that investing in data can change an organization.
  • Experience using dimensional data models.
  • Experience with Data Warehouses and especially ones leveraging common techniques like Kimball’s approach.
  • Experience using Python, R and/or SQL when working with data.
  • Strong technical capabilities and aptitude
  • Strong knowledge of application development concepts and practices.
  • Experience with continuous integration/delivery systems and/or practices.
  • Experience with Azure Data Lake, Snowflake, Jupyter Notebooks and/or Databricks are all big pluses.

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