Job VC
Middle Data Analytics Engineer
Technologies
Description
We are looking for a Middle 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, the company connects businesses with a network of independent couriers, providing access to fast, flexible, and efficient deliveries.
Project —
is focused on creating 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 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.
Must have:
3+ years of experience in SQL and data warehousing.
3+ years of hands-on experience with dbt Core and Airflow in production environments.
2+ years of experience working with reporting and data visualization tools such as Tableau, Looker, or equivalent.
Ability to foster a self-serve data culture and empower cross-functional teams with data.
Experience with Python and key data libraries such as pandas, numpy, matplotlib.
Experience with AWS S3, Redshift, Airbyte, dbt, Airflow, Castor, and Superset.
Strong communication skills in English, with the ability to translate complex data topics to both technical and non-technical stakeholders.
Responsibilities:
Build data pipelines and model data in the data warehouse to allow anyone across the business to interact with data at the level of detail they need.
Lead data projects from start to end, from requirement gathering to fostering adoption of newly created data assets.
Understand business developments and translate them into technical and data needs.
Propose improvements to data models and work together with the Data Platform team to improve the data toolkit.
Work together with 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.
Paid sick leaves up to 10 working days.
National holidays as time off up to 11 days.
Medical reimbursement or insurance after 3 months.
Online English courses.
Flexible working schedule and remote work.
Direct cooperation with the customer.
Communication with Top/Senior level specialists to strengthen your hard skills.
Online and offline teambuildings.
Volunteering culture development and support.
Project —
is focused on creating 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 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.
Must have:
3+ years of experience in SQL and data warehousing.
3+ years of hands-on experience with dbt Core and Airflow in production environments.
2+ years of experience working with reporting and data visualization tools such as Tableau, Looker, or equivalent.
Ability to foster a self-serve data culture and empower cross-functional teams with data.
Experience with Python and key data libraries such as pandas, numpy, matplotlib.
Experience with AWS S3, Redshift, Airbyte, dbt, Airflow, Castor, and Superset.
Strong communication skills in English, with the ability to translate complex data topics to both technical and non-technical stakeholders.
Responsibilities:
Build data pipelines and model data in the data warehouse to allow anyone across the business to interact with data at the level of detail they need.
Lead data projects from start to end, from requirement gathering to fostering adoption of newly created data assets.
Understand business developments and translate them into technical and data needs.
Propose improvements to data models and work together with the Data Platform team to improve the data toolkit.
Work together with 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.
Paid sick leaves up to 10 working days.
National holidays as time off up to 11 days.
Medical reimbursement or insurance after 3 months.
Online English courses.
Flexible working schedule and remote work.
Direct cooperation with the customer.
Communication with Top/Senior level specialists to strengthen your hard skills.
Online and offline teambuildings.
Volunteering culture development and support.