We are looking for a Middle Data Analytics Engineer to join our client’s team. Our client is a leading tech-enabled logistics platform transforming on-demand delivery across food, grocery, and retail sectors. Operating in over 130 cities across Europe, the company connects businesses with a network of independent couriers, providing fast, flexible, and efficient delivery services.
Project — is focused on building scalable analytics infrastructure and fostering a strong data-driven decision-making culture. The team works on improving data availability, reliability, and accessibility across different business functions and countries, reducing time-to-insight and enabling better business decisions. The role involves developing data pipelines, analytical models, and self-service analytics solutions using a modern data stack including AWS S3, Redshift, Airbyte, dbt Core, Airflow, Castor, and Superset.
Requirements:
2+ years of experience with SQL and data warehousing.2+ years of hands-on production experience with dbt Core and Airflow (mandatory).1+ years of experience with reporting and data visualization tools such as Tableau, Looker, or equivalent.Experience building and maintaining reliable data pipelines and analytical data models.Ability to foster a self-service data culture and empower cross-functional teams with data.Strong communication skills in English, with the ability to explain complex data topics to technical and non-technical stakeholders.
Responsibilities:
Build data pipelines and develop analytical data models within the data warehouse to enable accessible and detailed data analysis across the business.Lead data projects end-to-end, from gathering requirements to supporting the adoption of newly developed data assets.Understand business developments and translate business requirements into technical and data solutions.Propose improvements to existing data models and collaborate with the Data Platform team to enhance the data toolkit.Work closely with analysts to develop scalable reporting solutions.Promote data discovery and strengthen data knowledge across the company by creating comprehensive documentation and clear metrics definitions.Apply software engineering best practices to analytics workflows, ensuring data models are well-tested, documented, and maintainable.Support the development of a self-service data culture by enabling teams to independently access and analyze data.
We offer:
Vacation (up to 20 working days).Paid 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 and fully remote work opportunities.Direct cooperation with the customer.Communication with Top/Senior-level specialists to strengthen your technical skills.Online and offline team-building activities.Volunteering culture development and support.
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