Additionalinformation

Additional Information

For this role as an Analytics Engineer (m/f/d), the starting remuneration is as follows:

The base pay for this position is 65,000.00 - 75,000.00 EUR gross for full time (40 hours per week).

In addition, Flink offers the following benefits:

• A €1000 annual L&D budget as well as individual coaching options to ensure you have plenty of opportunities to learn, grow and achieve your goals
• 26 days of vacation, +1 day every year up to a maximum of 30 days
• A mobility budget of 35 EUR per month for Deutschland Ticket subsidy
• A discount on your Urban Sports Club membership
• Attractive company pension options
• Unlimited access to an e-learning and development platform, Prosus Academy, including online German courses
• Online discounts with Corporate Benefits and Future Bens
• A cool discount off your personal Flink orders; be the first to test out new products!
• A modern and dog-friendly office in the heart of Berlin - lots of delicious lunch spots available within short walking distance

It is our commitment that every applicant will be evaluated according to their skills regardless of age, gender identity, ethnicity, sexual orientation, disability status, or religion.

Companydescription

Company Description

Launched in 2021 with a simple yet bold mission, Flink set out to give people back their most valuable resource: time. We didn't just join the quick commerce race, we defined its potential. By enabling customers to order from a curated selection of over 3,000 groceries and household essentials through our user-centric app, we deliver what people need in minutes. We have fundamentally shifted the retail landscape across Germany and the Netherlands, while embedding sustainability into our core through an all-electric delivery fleet, recyclable packaging, and a focus on reducing food waste.

Today, Flink has evolved from a disruptive startup into a resilient and sustainable powerhouse. In an industry defined by rapid change, we’ve mastered the balance of hyper-efficiency and massive scale. With a network of around 160 hubs, we now bring the Flink experience to more than 22 million people, making us an integral part of the urban infrastructure. This impact is driven by a dedicated team of more than 10,000 colleagues, including a fully employed rider fleet that serves as the backbone of our operations. By generating over €550m in revenue in 2025, we have proven that our model is not only desirable but financially formidable.

Having built a proven foundation, we are now shifting from establishing our presence to accelerating our impact. Backed by prestigious partners like Prosus, Mubadala, Bond, DoorDash, Btomorrow Ventures and REWE, and fueled by fresh investment, we are entering our next major growth phase. We are thinking bigger, expanding our footprint, and refining every link in our value chain.

Our culture is defined by a shared bias for action and the commitment to being 1% better every day. We take ownership, stay close to the frontline, and support one another to ensure we never let another Flinker fail. We celebrate diversity and believe that our multicultural team is our greatest competitive advantage.

Are you ready to shape the future of quick commerce with us?

As an Analytics Engineer (m/f/d), you will be a key driver in evolving Flink’s data foundations. Part of the Analytics Engineering team embedded within the Operations department, you won't just "build reports" - you will act as a strategic thought partner for Customer Care, Operations, Finance, and Revenue teams.

You will own the end-to-end transformation layer, solving our most complex data challenges by turning raw signals into a trusted, scalable source of truth. Your goal is to ensure our data layer remains high-quality, performant, and easy to extend as we continue to scale. You will operate with a high degree of autonomy, owning the full lifecycle of your domain - from stakeholder relationships to the long-term evolution of the reporting landscape.

Jobdescription

Job Description

• Architect & Scale: Own the development of our transformation layer (dbt) and downstream surfaces (Looker/Lightdash). You will identify technical debt and implement modern approaches to ensure our foundations remain performant and easy to extend.
• Deep Stakeholder Partnership: Move beyond being an "executor of requests." You will work closely with business leaders to deeply understand their problems and proactively shape the data solutions they need.
• End-to-End Domain Ownership: Lead and evolve a major portion of our reporting landscape. You will be responsible for the health, accuracy, and roadmap of the data models serving our core business functions.
• Raise the Quality Bar: As a member of a growing team, you will champion engineering best practices: CI/CD, robust testing, and version control.
• Bridge Business & Tech: Act as the technical liaison between Product/Engineering and the business, ensuring our data infrastructure evolves in sync with our product growth without needing day-to-day oversight.

Qualifications

• A Business-First Engineer: You believe great analytics engineering starts with understanding the "why." You enjoy diving into the nuances of operations and finance to build better models.
• An Expert in the Modern Data Stack: You have extensive experience with SQL, dbt, and Looker (or similar BI tools), and a deep understanding of cloud data warehouses.
• Quality Obsessed: You take pride in building "trusted" data. You are an advocate for clean code, documentation, and rigorous testing.
• Strategic Communicator: You possess excellent English communication skills and the ability to drill down complex technical topics into actionable insights for business stakeholders.
• Expert in Data Modeling: You have mastery over SQL (preferably Google BigQuery) and extensive experience modeling tables with large, complex datasets. You understand how to build a transformation layer that is both performant and scalable.
• Proficient with the Modern Data Stack: You have proven experience using dbt to build robust SQL models and are comfortable working within Looker (including writing LookML) to build intuitive downstream surfaces.