Analytics Engineer

Posted 2 Days Ago
3 Locations
In-Office or Remote
Senior level
Professional Services • Consulting • Conversational AI • Generative AI • Infrastructure as a Service (IaaS)
Make Better Decisions, Faster—with Data That Works and AI to Activate It
The Role
Design and maintain scalable data models and end-to-end data marts, build and optimize ETL pipelines (dbt, Fivetran), ensure data quality and observability, collaborate with stakeholders to define KPIs, and use version control and whiteboarding tools to document and iterate on data products.
Summary Generated by Built In

Role Overview

We are seeking a highly skilled Analytics Engineer with a strong background in building data models, developing scalable architectures, and collaborating closely with stakeholders to translate business needs into actionable data solutions. This role is ideal for someone who thrives in fast-moving environments, enjoys direct interaction with stakeholders, and is passionate about testing, measuring usage, and ensuring observability of data marts.

🔑 Key Responsibilities

  • Data Modeling & Architecture:
    • Design, implement, and maintain robust, scalable data models to support analytics and reporting.
    • Build end-to-end data marts and ensure they meet stakeholder requirements for usability, accuracy, and performance.
  • ETL Development:
    • Build, optimize, and manage ETL pipelines using DBT (5+ years required) and tools like Fivetran.
    • Ensure high standards for data quality, integrity, and consistency across multiple sources.
  • Collaboration & Stakeholder Engagement:
    • Work directly with business stakeholders to gather requirements, define KPIs, and deliver usable data solutions.
    • Partner with at least one or two other analytics engineers to design, test, and refine data products.
  • Tooling & Process Management:
    • Use GitHub for version control and collaboration.
    • Leverage tools like Figma, FigJam, or Miro for whiteboarding and documenting data workflows.
    • Implement testing, usage measurement, and observability best practices for data marts.
  • Continuous Improvement:
    • Stay current with modern data stack trends and continuously improve data modeling methodologies.
    • Contribute to building the company’s long-term data modeling strategy and methodology.

🧩 Background & Skills

  • Mandatory Experience:
    • 5+ years working with DBT in production.
    • Experience with data in B2B SaaS, B2C digital products, CPG e-commerce, or health.
    • Proficiency with major cloud data warehouses (BigQuery or Snowflake).
    • Strong SQL skills and proven track record of scalable data modeling.
    • Hands-on use of GitHub for version control.
  • Collaboration Skills:
    • Proven experience working with other analytics engineers (not just as a solo data contributor).
    • Ability to work directly with stakeholders to design and deliver data products.
  • Preferred Experience:
    • Startup or smaller company background.
    • Work in consulting or agency environments.
    • Familiarity with BI tools like Looker or Tableau.
    • Experience with Python, dbt tests, and SQL linters like SqlFluff.

🌟 Traits & Mindset

  • Builder Mentality – Passionate about creating and iterating on data solutions from scratch.
  • Stakeholder-Centric – Comfortable leading conversations with non-technical users to gather requirements.
  • Analytical & Curious – Always measuring, testing, and improving data solutions.
  • Collaborative – Enjoys working closely with team members and cross-functional partners.
  • Time Zone Fit – Can work until at least 12 PM US Central Time.

Skills Required

  • 5+ years working with dbt in production
  • Experience with data in B2B SaaS, B2C digital products, CPG e-commerce, or health
  • Proficiency with BigQuery or Snowflake
  • Strong SQL skills and proven track record of scalable data modeling
  • Hands-on use of GitHub for version control
  • Build, optimize, and manage ETL pipelines using dbt and tools like Fivetran
  • Proven experience working with other analytics engineers
  • Ability to work directly with stakeholders to design and deliver data products
  • Ability to work until at least 12 PM US Central Time
  • Startup or smaller company background
  • Experience in consulting or agency environments
  • Familiarity with BI tools like Looker or Tableau
  • Experience with Python
  • Experience creating dbt tests
  • Experience with SQL linters like SqlFluff
  • Use of Figma, FigJam, or Miro for whiteboarding and documenting data workflows
Am I A Good Fit?
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The Company
25 Employees

What We Do

Turn Data Into Results—Fast. We help businesses turn data into decisions, revenue, and real impact—through tailored analytics and AI solutions. As a boutique consultancy, we deliver rapid, measurable outcomes without the bloat or buzzwords. Why Teams Choose BrainForgeAI: 🚀 Results in Weeks, Not Months – Fast-turnaround projects with clear ROI. 🤝 Flexible, Embedded Collaboration – We plug into your workflow and move as fast as you do. 🧠 Deep Expertise, Modern Stack – From Snowflake and dbt to GenAI and Rill, we build with what works. ✅ Proven with the Best – Trusted by Fortune 1000 firms and fast-growing startups alike. Our Services Include: 📊 Data Analytics & Reporting 🔄 ETL/ELT Development 🏗️ Data Modeling & Architecture 🤖 AI Implementation & Automation 📈 Customer-Facing Dashboards Let’s turn your data into your competitive edge. Reach out to explore how we can help. What Sets Us Apart: Quick wins with measurable impact - see results in weeks, not months Flexible, high-agency approach - we adapt to your needs and communication style Deep technical expertise across modern data stack (Snowflake, dbt, Rill) Proven track record with Fortune 1000 companies and high-growth startups Our Services: 📊 Data Analytics & Reporting 🔄 ETL/ELT Development 🏗️ Data Modeling & Architecture 🤖 AI Implementation 📈 Customer-Facing Dashboards Ready to transform your data into actionable insights? Let's connect! https://bit.ly/DiscoverBrainforge

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