Data Analytics Engineer

We're looking for a hands-on, engineering-forward Analytics Engineer who is obsessed with clean data, scalable pipelines, and turning complex data into decisions. You'll be the technical backbone of our data practice — owning our Snowflake warehouse, dbt Cloud transformations, and semantic layer, while partnering daily with Marketing and Finance to power the reporting and insights they depend on.

This is Amaze's first dedicated data hire, which means you'll have real ownership and real impact from day one. You won't be inheriting a playbook — you'll be writing it.

Our stack is modern and purposeful: Snowflake as our source of truth, Fivetran and Hightouch for data movement, dbt Cloud for transformation and semantic layer development, Tableau for reporting, and Google Analytics 360 / GA4 feeding into BigQuery. We're actively building out our dbt semantic layer to power AI-driven self-service analytics — including Slack-based chatbots that allow non-technical stakeholders to query data in natural language.

The person who joins us will own this infrastructure, grow it thoughtfully, and help the business actually use it.

Data Engineering & Infrastructure

• Own and maintain our Snowflake data warehouse, including warehouse sizing, cost management, and query optimization
• Build, maintain, and expand dbt Cloud data pipelines — from raw ingestion through staging, intermediate, and mart layers
• Manage ELT pipelines via Fivetran and Hightouch (reverse ETL), ensuring data is accurate, timely, and well-documented
• Partner with Engineering to ensure new product features are instrumented correctly and data flows cleanly from source to warehouse

Semantic Layer & AI Enablement

• Lead the continued buildout of our dbt semantic layer — defining shared metrics, governance standards, and source-of-truth definitions across business units
• Enable AI-powered self-service analytics tools (e.g., Slack-based chatbots) by ensuring the semantic layer is accurate, consistent, and well-governed
• Design metric definitions that serve both technical and non-technical consumers, so stakeholders can trust and explore data independently

Analytics & Reporting

• Serve as the primary data partner for Marketing and Finance — the two teams with the highest data demand at Amaze
• Build and maintain Tableau dashboards that translate complex data into clear, actionable insights for non-technical stakeholders
• Support conversion rate analysis, funnel optimization, and marketing performance measurement
• Develop and maintain executive-level reporting, including dashboards tracking company-wide KPIs

Data Culture & Governance

• Establish data definitions, documentation standards, and a request process so stakeholders know how to engage with the data team
• Drive self-service data literacy — reducing ad-hoc request volume by empowering teams with the tools and training to answer their own questions
• Ensure data considerations are part of every product and feature release, not an afterthought

Required

• 5+ years of hands-on experience in data engineering, analytics engineering, or a closely related role
• Strong, production-level experience with Snowflake — warehouse management, cost optimization, query tuning, and data modeling
• Deep experience with dbt Cloud — building and maintaining transformation pipelines, writing tests and documentation, and ideally hands-on work with the dbt Semantic Layer
• Proficiency in SQL at an advanced level; comfort with Python for scripting and pipeline support
• Experience with Tableau (or comparable BI tools) building dashboards for both technical and non-technical audiences
• Familiarity with ELT tooling such as Fivetran, and reverse ETL tools such as Hightouch
• Startup experience — you know how to operate without perfect requirements, prioritize ruthlessly, and move fast without breaking things

Strongly Preferred

• Experience with semantic layer tooling (dbt Semantic Layer, Cube, LookML, AtScale, or similar) — defining shared metrics and governing change across business units
• Experience supporting marketing analytics — attribution, funnel analysis, campaign performance, GA4/BigQuery pipelines
• Familiarity with AI-enabled analytics — LLM-powered self-service tools, natural language to SQL, or similar
• Experience with Google Analytics 360 / GA4 and integrating behavioral data into a warehouse
• Background integrating CRM data (e.g., HubSpot) and supporting Finance reporting workflows

Beyond the technical requirements, we're looking for someone who:

• Operates without a manager. You identify where the highest-impact work is, you prioritize it, and you see it through. No one will tell you what to do — and that energizes rather than unnerves you.
• Partners, not just produces. You work with marketing, finance, and product — not just for them. You ask questions, push back when data doesn't support a narrative, and help stakeholders understand their own business.
• Builds for the long term. You care about documentation, governance, and doing things right the first time — because you know you'll be the one maintaining it.
• Communicates clearly. You can translate technical data concepts into plain language for non-technical stakeholders, and you know when a Slack message is enough versus when a dashboard is better.

• Real ownership. You'll have significant influence over how we organize, model, and use data as a company — from day one.
• Modern stack. Snowflake, dbt Cloud, Fivetran, Hightouch, Tableau, GA4 — tools built for the way data teams work today.
• Meaningful problems. Marketing, Finance, Product, and Engineering all have real, pressing data needs. Your work will be visible and valued.
• Fast-moving startup. We're growing quickly and building a data-forward culture. This is a ground-floor opportunity.