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Manager, Business Analytics

Job in Charlotte, Mecklenburg County, North Carolina, 28245, USA
Listing for: Jobgether SRL
Full Time position
Listed on 2026-10-04
Job specializations:
  • IT/Tech
    Data Analyst, Data Warehousing, Data Engineering, Business Systems & Technology Analysis
Salary/Wage Range or Industry Benchmark: 130000 - 145000 USD Yearly USD 130000.00 145000.00 YEAR
Job Description & How to Apply Below

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Manager, Business Analytics based in the United States.

This role is a highly technical individual contributor position focused on turning complex data into actionable business insights and measurable outcomes. You will serve as a strategic analytics partner to Commercial, Finance, Operations, and other business functions, influencing decisions through advanced analytics and data-driven recommendations. The position sits at the intersection of business intelligence, data science, data engineering, and operational strategy.

You will design scalable analytical solutions using modern cloud data platforms, statistical methods, programming, and visualization technologies. The role also offers the opportunity to strengthen enterprise data quality, governance, reporting standards, and analytical capabilities. You will work closely with technical and business stakeholders in a fast-paced, purpose-driven environment where analytics directly supports operational performance and revenue growth. This is a remote opportunity within the United States.

Accountabilities:
  • Serve as the analytics lead for Commercial, Finance, Operations, and related business functions, providing technical expertise and strategic analytical guidance.
  • Act as a thought partner to operational and commercial leaders, helping prioritize analytics investments, establish success metrics, and measure business outcomes.
  • Partner cross-functionally to ensure analytical solutions align with strategic priorities and generate measurable business value.
  • Design, develop, and maintain scalable analytics solutions using SQL, Python, Snowflake, Tableau, Power BI, and modern cloud-based data platforms.
  • Conduct statistical analysis, forecasting, segmentation, hypothesis testing, predictive modeling, and exploratory data analysis to support business planning and operational decision-making.
  • Collaborate with Data Engineering, IT, and Master Data Management teams to define data requirements, improve data quality, optimize data pipelines, and strengthen enterprise data architecture.
  • Develop and maintain semantic data models, reusable datasets, KPI frameworks, and standardized metrics aligned with analytics governance standards.
  • Support enterprise data governance by validating source-system integrity, documenting metric definitions, monitoring data quality, and promoting consistency across reporting and analytics.
  • Apply AI, machine learning, and advanced analytics techniques where appropriate to improve forecasting, automate decision support, and uncover new business opportunities.
  • Translate complex analytical findings into clear narratives, insights, and recommendations that can influence leadership decisions and business strategy.
Requirements
  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Information Systems, Analytics, or another quantitative discipline.
  • 6--8 years of experience in advanced analytics, business intelligence, data science, revenue analytics, or a comparable technical analytical role.
  • Expert-level SQL skills, including complex joins, window functions, common table expressions (CTEs), query optimization, and dimensional data modeling.
  • Strong Python programming experience, including tools and libraries such as Pandas, Num Py, Sci Py, Stats Models, Scikit-Learn, and data visualization frameworks.
  • Strong understanding of data warehousing, ETL/ELT processes, data governance, and data quality management.
  • Experience with cloud data platforms such as Snowflake, Redshift, Databricks, Big Query, Azure Synapse, or similar technologies.
  • Hands-on experience with Tableau, Power BI, or…
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