Senior Analytics Engineer

Omaze; Deutschland; Remote; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

A cutting-edge startup in Germany seeks a Senior Analytics Engineer to manage the full analytics workflow, from ingestion to insights delivery. This role will involve building and testing data models, defining dimensions in BI tools, and presenting complex analyses to executives. Candidates should have 6-8 years of experience in analytics engineering, and expertise in SQL, Python, and modern data tools is crucial. Join a dynamic team committed to innovation in the gardening industry.

Qualifikationen

• 6-8 years in analytics engineering / data modeling / BI, including 2+ years owning production dbt pipelines.
• Deep expertise in Snowflake, dbt, SQL, Python, Git, and modern BI tools.
• Demonstrated success presenting complex analyses to execs and non-technical audiences.
• Strong business intuition in D2C or CPG, connecting data to revenue and margin.

Aufgaben

• Model & transform data: Build, document and test dbt models in Snowflake.
• Define dimensions/measures in Omni, maintain data-quality tests.
• Deliver intuitive Omni dashboards that surface actionable trends.
• Conduct cohort, pricing, promotion and inventory analyses.
• Own the narrative: Craft executive-ready decks and present to VPs and partners.
• Embed with Product, Retail and Ops squads to translate questions into data plans.

Kenntnisse

Analytics engineering

Data modeling

SQL

Python

Git

Snowflake

DBT

Business Intelligence tools

Ausbildung

Bachelor’s in a quantitative field

Jobbeschreibung

Role

Senior Analytics Engineer

Company Introduction

We’re a venture-funded, Boulder-based startup that’s reinventing the lawn and garden space through a lens of ecommerce and AI technology. Our data-driven, customer-focused services and products will help 90 million Americans turn their lawn into verdant and sustainable ecosystems. (Think custom meal kits for lawns, minus all the tedious chopping!)

We are backed by a group of experienced investors and advisors, and now we are looking for the right people to join our core team. Together, we will disrupt an industry by building cutting-edge greenfield products that help people and the environment.

If you don’t want to take our word for it, check out the article on us in Forbes magazine!

Job Description
As a Senior Analytics Engineer you’ll own the full analytics workflow—from ingestion and modeling in dbt, to defining the semantic layer in Omni, to crafting dashboards and delivering insights that move the business. You will partner with Product, Marketing, CX, Supply Chain/Ops and Finance, with a special focus on Sunday’s fast-growing Retail channel (Walmart, Home Depot, Amazon, regional partners). Reporting to the Principal, Data & Analytics, you’ll be equal parts architect, storyteller, and thought partner—designing performant data models and taking the spotlight to guide decisions in live forums.

Key Responsibilities

• Model & transform data: Build, document and test dbt models in Snowflake that power trusted DTC and Retail reporting.
• Semantic layer & governance: Define dimensions/measures in Omni, maintain data-quality tests and lineage, and champion data consistency.
• Dashboarding & self-service: Deliver intuitive Omni dashboards that surface actionable trends and empower teams to explore data independently.
• Advanced analytics: Conduct cohort, pricing, promotion and inventory analyses; design A/B test readouts; build Python notebooks that forecast and simulate outcomes.
• Present & influence: Own the narrative. Craft executive-ready decks, lead weekly/quarterly business reviews, and present live to VPs, C-suite and internal retail partners.
• Cross functional partnership: Embed with Product, Retail and Ops squads to translate fuzzy questions into data plans, surface opportunities, and drive roadmap decisions.
• Best-practice evangelism: Instill software-engineering rigor (CI/CD, Git, code review, dbt tests) and help shape Sunday’s modern data-stack strategy.

Desired Background

• 6-8 years in analytics engineering / data modeling / BI, including 2+ years owning production dbt pipelines.
• Deep expertise in Snowflake, dbt, SQL, Python, Git and a modern BI toolset (Omni or similar).
• Demonstrated success presenting complex analyses to execs and non-technical audiences—comfortable running the meeting, fielding questions, and influencing outcomes.
• Strong business intuition, ideally in D2C or CPG: you connect data to revenue, margin and operational levers.
• Bachelor’s in a quantitative field (Data/Computer Science, Engineering, Statistics, Economics) or equivalent practical experience.
• Bonus points if you have familiarity with retail point-of-sale feeds, media-mix/attribution modeling, or supply-chain optimization.

Competencies

• SQL craftsmanship & data modeling – dbt concepts and best practices, fluency with Kimball/star schemas, and incremental patterns
• Executive presence & storytelling – turns analysis into compelling narratives and confidently presents to VP/C-suite audiences.
• Collaboration & influence – builds trust across functions and drives alignment on data-informed decisions.
• Ownership & bias for action – thrives in a fast-growing startup, prioritizes ruthlessly, delivers with limited guidance.
• Quality mindset – implements CI/CD, code review, and observability to keep pipelines reliable.

Other Skills and Qualifications

• Desire to lead, shape, and have ownership of a hyper-growth company
• Self-directed, team-oriented, and customer-centric
• Ability to prioritize and drive many projects simultaneously with sense of urgency
• Roll up the sleeves, can-do spirit! You look forward to being part of a small, scrappy team and are willing to pitch in with whatever needs to get done

As a company rooted in nature, we deeply understand the benefits of diversity. We work to build a culture that attracts a diverse mix of talented people to help us bring lawn care out of the dark ages. We are committed to building a diverse, vibrant team that brings determination and passion to our work everyday.