Middle Data Analytics Engineer

We are seeking a Data Engineer for a leading tech-enabled logistics platform that transforms on-demand delivery across sectors like food, grocery, and retail. Operating in over 130 cities across Europe, they are connecting businesses with a network of independent couriers, providing access to fast, flexible, and efficient deliveries.
A goal is to create a modern standard for urban deliveries that addresses environmental and social challenges while providing a premium delivery experience through speed, flexibility, and convenience.

The team is focused on developing a strong data-driven decision-making culture by improving the availability, reliability, and accessibility of data across teams and countries. The objective is to reduce time-to-insight and enable better business decisions through scalable analytics solutions.

As an Analytics Engineer, the role involves working closely with key products and business initiatives from a data perspective. Responsibilities include building high-quality data pipelines and analytical models, applying software engineering best practices to analytics workflows using dbt, and maintaining well-tested and documented data models within the data warehouse.

The position also contributes to the development of a self-serve data culture, helping teams independently access and analyze data through appropriate tools and scalable analytics infrastructure.

Requirements:

• 2+ years of experience in SQL and data warehousing
• 2+ years of hands-on experience with dbt core and Airflow in production environments (mandatory)
• 1+ years of experience working with reporting and data visualization tools such as Tableau, Looker, or equivalent
• Experience with Python and key data libraries (e.g. pandas, numpy, matplotlib) is a plus
• Ability to foster a self-serve data culture and empower cross-functional teams with data
• Strong communication skills in English; capable of translating complex data topics to both technical and non-technical stakeholders
• Our Data stack is made up of AWS S3, Redshift, Airbyte, dbt, Airflow, Castor and Superset.

Responsibilities:

• Build data pipelines and model data in our data warehouse, to allow anyone across the business to interact with data in the level of detail they need
• Lead data projects from start-to-end, from requirement gathering to fostering adoption of the newly created data assets
• Understand the developments in the business, and translate them to technical / data needs
• Propose improvements to our data models and work together with the Data Platform team to improve our data toolkit
• Work together with our analysts to build scalable reporting. Foster data discovery and strengthen data knowledge across the company by writing comprehensive documentation and metrics definitions.

We offer:

• Vacation (up to 20 working days)
• Sick leaves (10 working days)
• National Holidays as time off (up to 11 days)
• Medical reimbursement/insurance after 3 months
• Online English courses
• Flexible working schedule, remote
• Direct cooperation with the customer
• Communication with Top/Senior level specialists to strengthen your hard skills
• Online/offline teambuildings
• Volunteering culture development and support.