Data Engineer

About Us

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We are on the lookout for a Data Engineer to join the Quick Commerce team on our journey to always deliver amazing experiences.

About the Role

As a Data Engineer, your primary mission will be to contribute to forming and improving our huge data model setup located in Google Cloud. This involves diving deep into our data platform to break down data platform and pipeline complexities, identify friction points, and optimise systems for better performance and scalability. You will be part of the team directly responsible for managing the data platform’s infrastructure components, continuously monitoring and optimizing pipelines, queries, and databases to ensure high availability and performance.

Day-to-day, you will be hands-on in designing, building, and maintaining scalable ingestion and data pipelines, ETL processes using SQL and Python, with a strong focus on ensuring high data quality, integrity, and low latency. You will be responsible for promoting best coding practices and participating in standardization routines for data foundations, analytics, and data science. This extends to collaborating on data catalogs and access controls to ensure all data processes adhere to strict accuracy, privacy, security, and compliance standards.

You will work as a key collaborator, establishing Data Contracts between our numerous Domain Data Units and shaping efficient ways of working between various stakeholder groups. You will also work closely with cross-functional teams to define data requirements and implement or enhance data models specifically for our DataMesh environment.

Responsibilities

• Manage data platform’s infrastructure components, continuously enhancing and monitoring them as well as optimizing pipelines, queries, and databases for high availability and performance.
• Design, build, and maintain scalable data pipelines and ETL processes using SQL and Python, ensuring high data quality, integrity, and low latency.
• Work with cross-functional teams to define requirements and implement/enhance data models for a DataMesh environment.
• Collaborate on data catalogs and access controls, ensuring all data processes adhere to accuracy, privacy, security, and compliance standards.
• Build and deploy foundational data products for data science and analytics teams, troubleshoot data quality problems, and provide technical support for the BI toolbox.

You’ll help build technology that scales our non-food offerings, reaching new market segments and driving revenue growth.

Qualifications

• 3+ years of experience in data or analytics engineering or a related field, with a focus on developing and maintaining large-scale data pipelines.
• Proven ability to design and build complex data modeling in DataMesh.
• Strong programming skills in SQL, Python.
• Experience with implementing the Data Mesh model in a production environment, along with Data Lakes.
• Experience with data visualization tools such as Tableau, Looker, or Power BI.

Benefits

• 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 will support you in developing yourself and your career growth opportunities: 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform to explore a variety of online courses.
• Health Checkups, Meditation, Gym & Bicycle Subsidy
• 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
• The power of getting together over some food is unrivaled. Digital Meal Vouchers, Food Vouchers, Corporate Discounts.
• You can also visit our relocation hub and check out more information about moving to Berlin.
• We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience—just let us know with an email to our Inclusion Officer at E-Mail auf jobs.smartrecruiters.com ansehen.