Application Guide
How to Apply for Analytics Engineer
at Supplyhouse
🏢 About Supplyhouse
SupplyHouse.com is an industry-leading e-commerce company specializing in HVAC, plumbing, heating, and electrical supplies, operating since 2004 with a strong 'people first' culture. Their core values—Generosity, Respect, Innovation, Teamwork, and GRIT—create a supportive, diverse remote environment where team members are empowered to grow. This is a chance to join a stable, values-driven company that is investing in modern data infrastructure to better serve customers and internal teams.
About This Role
As an Analytics Engineer on the Finance team, you will design and build SupplyHouse’s production data layer from the ground up in BigQuery, owning the transformation layer between raw data and reporting. You’ll turn complex data into clean, tested, and well-documented datasets, standardize core business metrics, and enable trusted self-service analytics across the organization. This is a high-impact role where you’ll partner with engineers, analysts, and business stakeholders to make high-quality data accessible and actionable.
💡 A Day in the Life
You’ll start your day with a stand-up with the data team, then dive into building or optimizing dbt models in BigQuery to support a new finance dashboard. Later, you might meet with finance analysts to refine metric definitions, write documentation for a dataset, or review a pull request from a colleague. You’ll also spend time troubleshooting data quality issues and ensuring that the transformation layer is reliable and well-tested.
🚀 Application Tools
🎯 Who Supplyhouse Is Looking For
- 3+ years of experience in analytics engineering, data engineering, or a related role, with deep hands-on expertise in BigQuery and SQL.
- Proven ability to design and build scalable data transformation layers using tools like dbt, including writing tests, documentation, and version-controlled models.
- Strong understanding of data modeling best practices (star schema, normalization, slowly changing dimensions) and experience standardizing business metrics.
- Comfortable collaborating cross-functionally with finance, engineering, and business teams, and able to translate complex data concepts for non-technical stakeholders.
- Self-motivated and thrives in a remote work environment, with excellent communication skills and a commitment to SupplyHouse’s core values.
📝 Tips for Applying to Supplyhouse
Highlight specific projects where you built a data layer from scratch in BigQuery, including the tools used (e.g., dbt, Airflow) and the impact on business reporting.
Emphasize any experience you have with finance data or supporting finance teams, as this role sits within the Finance department and will involve financial metrics.
Showcase your ability to document and test data models—mention dbt tests, data dictionaries, or other documentation practices you’ve implemented.
Demonstrate familiarity with SupplyHouse’s core values (GRIT, Generosity, Respect, Innovation, Teamwork) by weaving them into your cover letter or resume summary.
Since the role is remote, provide examples of how you’ve successfully collaborated remotely with cross-functional teams and maintained high productivity.
✉️ What to Emphasize in Your Cover Letter
['Your hands-on experience building and maintaining a production data layer in BigQuery, including specific tools and techniques used.', 'How you’ve standardized business metrics and enabled self-service analytics for non-technical stakeholders, ideally in a finance context.', 'Your alignment with SupplyHouse’s core values and your ability to thrive in a remote, people-first culture.', 'A concrete example of a complex data problem you solved and how it improved data trust or decision-making.']
Generate Cover Letter →🔍 Research Before Applying
To stand out, make sure you've researched:
- → Explore SupplyHouse.com’s e-commerce platform to understand their product catalog, customer base, and how data might drive business decisions.
- → Research the HVAC, plumbing, heating, and electrical supplies industry to grasp common metrics and challenges (e.g., supply chain, pricing, customer retention).
- → Look into SupplyHouse’s core values and recent news or blog posts to understand their culture and any recent data initiatives.
- → Investigate common data stack tools for analytics engineering (e.g., dbt, BigQuery, Fivetran) and be prepared to discuss how you’ve used them.
💬 Prepare for These Interview Topics
Based on this role, you may be asked about:
⚠️ Common Mistakes to Avoid
- Focusing only on technical skills without demonstrating how you’ve partnered with business stakeholders to deliver actionable insights.
- Neglecting to mention specific tools like BigQuery or dbt—generic data engineering experience isn’t enough for this role.
- Ignoring the finance context—failing to show any interest or experience in financial data or metrics could make you seem less aligned with the team’s needs.
📅 Application Timeline
This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.
Typical hiring timeline:
Application Review
1-2 weeks
Initial Screening
Phone call or written assessment
Interviews
1-2 rounds, usually virtual
Offer
Congratulations!