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Salary
≈ $34k – $100k per year (Estimated)
Location
Hybrid (São Paulo, Brazil)
Seniority
Senior · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 2, 2026. First seen by Alion on Sep 23, 2026. Mars scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Mars, Incorporated is a family-owned global maker of confectionery, snacks, food and pet care products headquartered in McLean, Virginia, with brands such as M&M's, Snickers, Orbit, Pedigree and Whiskas as well as veterinary services. Founded in 1911 and still owned by the Mars family, it operates worldwide; the job board on this record covers its business in Russia, which includes factories such as Stupino near Moscow and a national sales force. Its Russian vacancies include territory and key account managers, sales representatives, brand managers, finance analysts, site IT and process engineers, food safety specialists and logistics coordinators.

Job Description:

We are looking for a proactive, analytical, and customer-focused Senior Reporting Analyst to lead the design and delivery of high-impact BI solutions. In this role, you will combine deep technical expertise in Power BI and dimensional modeling with a keen interest in modern data engineering practices.

You will serve as a key bridge between internal customers and cloud data engineering teams-translating complex operational challenges and requirements into intuitive, high-performance executive dashboards while optimizing how data flows from the Lakehouse layer into semantic models.

Key Responsibilities

  • Lead Requirements Discovery & Advisory:
  • Facilitate discovery workshops with internal customers and cross-functional teams to define KPIs, reporting logic, and dashboard UX wireframes.
  • Confidently advise internal customers on data visualization best practices, cognitive ergonomics, and user-centric analytical design.
  • Architect Robust Semantic Models & Dashboards:
  • Build scalable, high-performance Star Schema models (Fact and Dimension structures) adhering to enterprise modeling standards.
  • Author sophisticated DAX calculations, including complex time-intelligence patterns, dynamic metrics, semi-additive calculations, and Row-Level Security (RLS).
  • Design clean, executive-ready dashboard visualizations that drive actionable decision-making for your internal customers.
  • Optimize Performance & Transformation Placement:
  • Evaluate transformation placement across the entire pipeline (Source vs. Lakehouse vs. Power Query/DAX) to preserve query folding and maximize refresh efficiency.
  • Diagnose and resolve report and visual latency using tools such as Power BI Performance Analyzer, DAX Studio, and VertiPaq Analyzer.
  • Collaborate with Data Engineering:
  • Partner with Data Engineers to shape upstream Lakehouse tables, validate pipeline outputs, and ensure semantic models consistently meet internal customer service-level expectations.

Qualifications & Experience

Essential Experience:

  • 3-5+ years of dedicated, hands-on experience designing and developing enterprise Power BI solutions, semantic data models, and executive dashboards.
  • Expert Dimensional Modeling: Proven ability to build performant Star Schemas from multi-source enterprise environments.
  • Advanced DAX & Power Query (M): Deep expertise writing maintainable DAX measures, implementing dynamic security (RLS/OLS), and leveraging Power Query with full query folding awareness.
  • Transformation Architecture: Clear understanding of where transformations belong across the stack to ensure scalability and cost-efficiency.
  • Customer Engagement & Advisory: Proven experience leading requirements discussions, managing expectations, and presenting analytical insights directly to internal customers and leadership.

Nice to Have (High Advantage):

  • 2+ years of practical experience working with SQL and modern cloud data architectures (e.g., Azure Databricks, Azure Data Lake / ADLS Gen2, Snowflake).
  • Databricks Integration: Hands-on experience connecting Power BI to Azure Databricks (Delta tables, Databricks SQL Warehouses) with a solid grasp of storage modes (Import, DirectQuery, and Composite Models).
  • Data Engineering Awareness: Familiarity with Delta Lake concepts/optimizations (e.g., Z-Ordering, Liquid Clustering) and cloud orchestration tools (e.g., Azure Data Factory).

Core Competencies & Mindset

  • Information Passion: Genuine enthusiasm for data storytelling, UI/UX clarity, and empowering internal customers through intuitive visual analytics.
  • Continuous Learner: Strong curiosity to explore upstream data engineering patterns, Lakehouse architectures, and emerging analytics tools.
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