Analytics Engineer

As an Analytics Engineer on the Retail Store Analytics team, you will help build and maintain the analytic data pipelines that empower the analytics and reporting key to decision making across Retail

• Design, create, refine, and maintain data pipelines and ingestion processes
• Collaborate with other data scientists, analysts, and engineers to build full-service data solutions
• Work with multi-functional business partners and vendors to acquire and transform raw data sources
• Develop a deep understanding of retail customer base and purchase choices
• Analyze data covering a wide range of information from financial reporting to device purchase patterns
• Design, develop, validate and maintain big data-driven predictive models, tools and pipelines to improve device export predictions
• Use data observability tools to develop and manage and automate testing, alerting and improve data quality
• Collaborate with data science, product, and engineering groups to translate business needs into data requirements
• Work with production teams to handoff reporting requirements for data products and communicate sophisticated concepts and the results of the analyses in a clear and effective manner to business partners

• 4+ years of industry experience building analytics pipelines in a production development environment
• Bachelor’s degree in Computer Science, Electrical Engineering, Information Systems, Data Science or other Analytics fields, or a related subject area, or equivalent industry experience
• 4+ years coding in SQL or PySpark and Python
• 4+ years in data modeling and building robust and scalable data processes and pipelines for modeling, analysis, and reporting
• Ability to initiate, refine, and complete projects with minimal guidance
• Ability to think critically and collaborate multi-functionally with other data engineering, data science and analytics partners distilling abstract requirements into clear data products

• Comprehensive medical and dental coverage
• Retirement benefits
• Range of discounted products and free services
• Reimbursement for certain educational expenses
• Discretionary bonuses or commission payments
• Relocation assistance

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