Staff Analytics Engineer - Consumer Product (all genders)

Company Description

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in over 70+ countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, we enable creative minds to deliver solutions that create impact within our ecosystem. We move fast, take action and adapt. No matter where you're from or what you believe in, we build, we deliver, we lead. We are Delivery Hero

Job Description

We are on the lookout for a Staff Analytics Engineer (all genders) to join one of our Consumer product tribes that builds and scales the digital experience enjoyed by millions of consumers across 11  brands in 70+ countries. Our users can do a lot on our platform—order food delivery, buy groceries, find dine-in deals, discover new ad offerings from our partners, play games in our loyalty program (and more!)—and our goal is to make all this as delightful, personalised and seamless an experience as possible!

This is a hybrid role embedded within our consumer analytics team. You will be acting as a bridge between product analytics teams, data engineering teams, and external data teams with the goal of enabling shorter time to insights for the analytics team, improving data trustworthiness  as well as enabling greater self-serve for both analysts and end-users alike. The person taking on this challenge is required to be a self-starter with a strong growth and get-things-done mindset. You will be expected to identify root causes of analytics pain points, propose and drive solutions with external teams towards addressing them, and be comfortable getting hands-on or implementing quick fixes to unblock the business while not losing sight of the longer term vision.  

This role is based in Berlin and the team is structured as cross-functional squads & tribes that focus on different aspects of our user experience. 

40% Data Architecture, Data modeling & Data pipelines building:

• Proactively identify analysts' pain points and understand data use cases. 

• Work with analytics managers to create an analytics data blueprint and execution plan

• Propose and create data models, work with data engineers to productionize models that reduce time to insights, enable reliable experiment evaluation and greater end user self-serve capabilities.

• Understand gaps in the current DBT & Airflow framework for analytics use cases, work with  data engineering teams to improve the setup

40% Data steward and data management

• Create a data quality monitoring, alerting and resolution strategy, work with the support of internal data teams to implement data quality monitoring and alerting

• Participate in data steering committee meetings and work with external data stakeholders to address data quality issues and improve data accessibility

• Champion quality data governance, create data processes that improves data governance while balancing business agility

• Act as a 2nd layer of support for investigating data quality issues

20% Documentation and communication

• Create and track metrics to showcase the impact of data initiatives

• Track data issues and manage communication to ensure key stakeholders are informed

• Maintain good documentation of our data and data processes

Qualifications

• 4+ years of relevant analytics/data engineering experience in rapidly growing and dynamic environments

• Solid production-grade experience with workflow management tools (primarily Airflow) and config-driven data build tooling (primarily DBT)  to deliver end-to-end data pipelines.

• Strong skills in schema design, dimensional data modeling, SQL and working with large datasets

• Experience with enabling data quality observability,monitoring and alerting.

• Ability to drive and manage medium scale project initiatives and work with external teams on larger projects

• Basic experience with data visualization tools (Looker, Tableau)

• You aim for clean and well engineered solutions, while keeping an eye for simplicity and pragmatism.

• You are highly passionate about data, with creative problem-solving abilities and an eye for detail.

• You have good English communication skills; being able to explain to the team complex technical projects, and to summarize them for non-technical stakeholders.

• You take ownership of your tasks and support the team embracing sharing and collaboration.

Nice to have

• Familiarity with BigQuery and Google Cloud Platform

• Familiarity with data quality tooling (great expectations, Monte Carlo)

• Familiarity with experimentation tooling and techniques (Eppo)

• Python

Additional Information

Ensuring you and all our Heroes are looked after, happy, and healthy is always on the menu. Because if you’re in good shape, then we’re in good shape.

• Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week

• We offer 27 days holiday with an extra day on 2nd and 3rd year of service

• Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation, Yoga, Gym & Bicycle Subsidy

• Cash. Dough. Cheddar. Whatever you call it, we’ll help you with it: Employee Share Purchase Plan, Sabbatical Bank,  Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan

• Look up and go for it. We will support you in developing yourself and your career: 1.000 € Educational Budget, Language Courses, Parental Support

• The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers, Food Vouchers, Corporate Discounts and access to the Udemy Business platform to explore a variety of online courses.

We believe diversity and inclusion are key to creating not only an exciting product, but also an amazing customer and employee experience. Fostering this starts with hiring - therefore we do not discriminate on the basis of racial identities, religious beliefs, color, national origin, gender identities or expressions, sexual orientations, age, marital or disability statuses, or any other aspect that makes you, you. We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience—just include it in your application. You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.