Business Intelligence Analyst

GLDN

$80K — $110K *
Business Services
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in business intelligence or data analysis, engaging multiple functions like marketing and finance.
  • E-commerce and operations experience, with a preference for knowledge in marketing attribution and supply chain analytics.
  • Strong business acumen with the ability to translate complex issues into actionable insights.
  • Capability in scientific problem solving, developing robust hypotheses, and validating findings.
  • Technical proficiency in SQL, statistics knowledge, and familiarity with data modeling.
  • Experience with modern data stacks like Snowflake and dbt models.
  • Hands-on experience with BI tools, especially Sigma, in creating advanced dashboards.

Responsibilities

  • Act as a dedicated data partner to business stakeholders, diagnosing challenges and proposing solutions.
  • Design and maintain intuitive dashboards and integrated workflows for core business operations.
  • Advise on the design and maintenance of data models in the data warehouse.
  • Conduct independent analysis using SQL, statistics, and Python, identifying trends and backing business hypotheses.
  • Empower business users to effectively leverage self-service data and promote metric consistency.

Benefits

  • Professional development opportunities and exposure to modern analytics tools.
  • Collaborative environment working alongside business leaders across various functions.
  • Autonomy to own projects and drive analytical solutions.
Full Job Description
Description

Role Overview

We are looking for a mid-to-senior level BI Analyst who can independently investigate complex business problems across marketing, ecommerce, operations, inventory, product, and finance, identify root causes, communicate insights clearly, and build scalable reporting and analytical solutions that drive action. While reporting directly to the Head of Data & Analytics, you will also serve as a strategic partner to business leaders across the organization-not only providing information, but advising on decisions and helping shape the processes through which those decisions are executed.

This role requires a unique balance of business acumen, independent problem-solving, and technical expertise. You will own our analytics front end (Sigma), work comfortably within our Snowflake data warehouse, and leverage data analysis, visualization, and monitoring to solve complex business challenges.
Key Responsibilities
  • Business Partnership & Requirement Gathering: Act as a dedicated data partner to business stakeholders. Meet regularly with teams to diagnose operational challenges, gather requirements, and proactively propose analytical solutions without needing explicit step-by-step direction.
  • BI Development & Automation: Design, build, and maintain intuitive dashboards, interactive tables, automated alerts, and integrated workflows to support core business functions. Own and implement reporting standards across our Sigma instance.
  • Data Modeling & Transformation: Collaborate with our broader data team to advise on the design and maintenance of data models in our warehouse
  • Independent Analysis & Experimentation: Utilize SQL, basic statistics, and Python to conduct independent deep-dives, identify trends, and back up business hypotheses with rigorous descriptive and prescriptive analytics.
  • Data Literacy & Governance: Empower business users to leverage self-service data in Sigma safely and effectively, acting as a champion for metric consistency across the organization.


Requirements

Qualifications
  • 5+ years of work experience in business intelligence, data analysis, or a highly analytical business role, with demonstrated experience analyzing business performance across multiple functions, including marketing, ecommerce, product, operations, inventory, finance, or supply chain.
  • E-commerce & Operations Exposure: General experience with e-commerce and manufacturing/ERP data required. Specific experience with marketing attribution models and supply chain analytics highly preferred.
  • Business Acumen & Fluency: Ability to move fluidly between executive-level business questions and detailed data analysis, translating ambiguous problems into actionable recommendations.
  • Scientific Problem Solving: A strong foundational habit of formulating clear hypotheses, systematically interrogating datasets to isolate variables, and validating findings with logical rigor before drawing conclusions.
  • Technical Breadth: Foundational knowledge of statistics (e.g., hypothesis testing, descriptive stats), experimental design, and A/B testing. Proficiency with SQL. Familiary with dimensional modeling best practices. Familiarity with at least one data exploration and analysis language (R, Python, etc).
  • Modern Data Stack Experience: Reasonable capability working with Snowflake (or equivalent) and navigating dbt models.
  • Mastery of modern BI tools: Deep, hands-on experience developing advanced, interactive dashboards, alerts, and automations, with modern BI tools such as Tableau, Power BI, Looker, Sigma, Omni, etc. Experience with Sigma highly preferred.
  • AI-Native: Hands on experience with using generative AI and agentic AI applications to enhance business intelligence workflows.
  • Understanding User Behavior: Demonstrated ability to anticipate how users will interact with a data product and what will be most useful for focusing their attention and driving decisive action.
What Makes You a Great Fit
  • You know our tools and data: You bring experience with modern data tooling and with the types of data that are core to our business (marketing, e-commerce, production, supply chain, customer service).
  • You're an investigative problem solver: You don't just build what people ask for; you ask "why" until you understand the root symptom, then build what they actually need.
  • You're an autonomous executor: You don't need a detailed feature list to get to work. Once given a strategic direction or a general problem to solve, you are excited to jump in, talk to the team, figure out what's actually broken, and own the solution end-to-end.
  • You're a translator: You excel at bridging the gap between technical data layers and non-technical business concepts.
  • You're highly curious: You constantly experiment with new tools and methodologies, and you stay up to date with emerging technologies, particularly AI.
  • You value data trust: You care deeply about accuracy, knowing that a broken dashboard or an incorrect metric breaks trust with the business.

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