Analytics Engineer

Analytics Engineer

Vari, originally known as VariDesk®, started the standing desk revolution. Now in its 13th year, Vari's mission is to create workspaces that elevate people. With millions of fans and a complete line of over 400 office furniture products in the market today, Vari is continuing to simplify and disrupt the office furniture industry by pioneering a direct B2C and B2B business model, reimagining how workspaces are defined, designed, and delivered.

Vari is looking for an analytically driven Analytics Engineer to join our Technology Team. In this role, you will be the primary owner of business intelligence and data analytics at Vari, turning our data into clear, trusted, and actionable insight that fuels smarter decisions across the business. You will work across a modern AI-forward analytics stack to deliver statistical analysis, self-service reporting, and advanced dashboards, while also contributing to the SQL Server data warehouse foundations that power them. Critically, you will serve as a bridge between our data capabilities and our business teams as someone who understands not just the data, but the business context behind it.

This is a high-visibility, high-impact individual contributor role on a lean data team that is actively investing in its analytics and AI capabilities. Most of your time (~75%) will be spent doing what you do best: digging into data, surfacing trends through statistical analysis, and delivering Power BI reports and dashboards that stakeholders use and trust. The remaining focus (~25%) supports the data engineering side, contributing to star schema design, T-SQL stored procedures, and ETL pipelines that feed clean, reliable data into the warehouse.

This role demands equal parts technical depth and business fluency. You will work directly with leaders and teams across Sales, Operations, Finance, and Marketing, earning their trust by understanding their goals, asking the right questions, and delivering analysis that drives real decisions. If you're energized by working at the intersection of rigorous analysis and modern data tooling, and excited by the opportunity to embed AI-powered analytics into the way a growing company understands itself, this role is built for you.

Key Responsibilities

Business Intelligence & Analytics

• Lead the design and delivery of dashboards, reports, and analytical products using Power BI and other modern BI tools
• Apply statistical analysis techniques, including regression, forecasting, segmentation, cohort analysis, and hypothesis testing, to surface meaningful patterns and trends
• Build and maintain advanced data models incorporating DAX, calculated measures, and KPI frameworks aligned to business strategy
• Serve as a trusted analytics partner to business stakeholders across Sales, Operations, Finance, and Marketing, proactively identifying opportunities where data can drive better decisions
• Lead requirements-gathering conversations with business teams; translate ambiguous or complex business questions into well-scoped analytical problems and clear deliverables
• Present analytical findings and recommendations confidently to both technical and non-technical audiences, including senior leadership
• Leverage AI and machine learning capabilities within the BI stack (e.g. Power BI Copilot, Azure AI, Python- or R-based ML models) to augment analysis and automate insight delivery
• Use Python or R (e.g. pandas, NumPy, scikit-learn, statsmodels, tidyverse, caret) for exploratory data analysis, statistical modelling, and scripted reporting workflows
• Champion self-service analytics by publishing governed well-documented semantic models and training end users across the business
• Monitor report adoption, data quality, and metric consistency; proactively identify and resolve discrepancies
• Document metric definitions, analytical methodologies, and report lineage to promote a data-literate culture

Data Engineering

• Contribute to the design and build of star schema structures in SQL Server, including dimension tables, fact tables, and aggregate layers
• Write and maintain T-SQL stored procedures and ETL logic supporting staging-to-DWH data flows
• Integrate data from key source systems including Salesforce CRM and other operational platforms
• Support source-to-target mapping documentation and data lineage tracking for new data domains
• Collaborate with the broader data team on pipeline reliability, performance tuning, and warehouse architecture

Required Qualifications & Skills

• 3+ years of experience in analytics engineering, BI, or data analyst role with demonstrable statistical depth
• Strong proficiency in SQL Server and T-SQL for data querying, transformation, and analysis
• Advanced Power BI skills, including DAX, Power Query, semantic modelling, and row-level security
• Working knowledge of Python or R for data analysis and statistical modelling (e.g. pandas, scikit-learn, tidyverse, ggplot2, or similar)
• Hands-on experience with statistical analysis techniques such as forecasting, regression, segmentation, or A/B testing
• Demonstrated business acumen, the ability to connect data findings to business outcomes and communicate their strategic relevance
• Proven track record of managing stakeholder relationships: gathering requirements, setting expectations, and delivering analytical work that earns trust
• Experience working with Salesforce data as a reporting or analytical source
• Familiarity with dimensional modelling concepts and star schema design
• Exceptional communication skills, able to translate complex analysis into clear, compelling narratives and recommendations for non-technical audiences

Nice to Have

• Experience with modern BI and analytics tools beyond Power BI, such as Tableau, Looker, Metabase, or Sigma
• Exposure to AI/ML-augmented analytics (e.g. Power BI Copilot, Azure OpenAI, Databricks AI, or LLM-based insight tools)
• Familiarity with cloud data platforms such as Azure Synapse Analytics, Snowflake, BigQuery, or Databricks
• Experience with dbt for data transformation and semantic layer development
• Knowledge of notebook-based analytics environments (Jupyter, RStudio, Azure Notebooks, or Databricks Notebooks)
• Version control experience with Git for SQL, Python, R, and BI asset management
• Exposure to data observability tools (e.g. Monte Carlo, Great Expectations, dbt tests)
• Familiarity with Agile or Scrum delivery frameworks

Why Vari:

• Short-term and long-term incentive plan
• 401k and profit-sharing plan
• On-site gym, spa-like locker room
• Enhanced paternity, maternity, and adoption programs
• Personal and volunteer time off
• Team building events on and off-site
• Mentoring and career development
• Education reimbursement
• Wellness program and insurance premium discounts
• At-home work set-up