Senior Lead, Business Intelligence

Skills
SQL Server Reporting ServicesAnalyticsBusiness IntelligenceData AnalyticsData VisualizationLookmlLooker
Role

What the job involves

The main requirements, responsibilities and hiring steps.

Requirements

  • Bachelor's degree in Statistics, Computer Science, MIS, or similar quantitative field preferred.
  • 4+ years of relevant experience as a data analyst, data engineer, IB developer or BI analyst.
  • Experience with Microsoft Azure and Google Cloud Platform preferred.
  • Hands-on development experience with reporting tools like Power BI, SSRS, Tableau, Looker, and QlikSense.
  • Solid experience in scripting with SQL, Python, JSON, LookML, and/or R.
  • Solid understanding of best engineering practices for the full software development life cycle (SDLC).
  • Deep understanding of data warehousing concepts, database designs and data architecture.
  • Experience with big data technologies and advanced data analytics.
  • Good written and verbal communication skills.
  • Strong analytical and problem-solving skills.
  • Demonstrated strong interpersonal skills.
  • Ability to work in a fast-paced environment concurrently on multiple projects.
  • Commitment to excellence, quality, detail, and deadlines.
  • Ability to work independently without frequent direction.
  • Entrepreneurial mindset and ownership attitude.

Day to day

  • Build and maintain reporting and insights systems that support our business requirements.
  • Transform insights from large data sets into strategic opportunities.
  • Collaborate closely with stakeholders in Field Operations and Service Assurance to define and meet business requirements.
  • Design, develop, and maintain reporting infrastructure using tools like Power BI, SSRS, Tableau, Looker, and QlikSense.
  • Lead efforts to apply software engineering best practices to analytics solutions and ensure accurate data for business consumption.
  • Conduct research and analysis of business situations to contextualize and summarize data for end users.
  • Create reusable datasets for analysis by other analysts.