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.
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.
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