Data Engineer/DataOps

We are looking for a Data Engineer to join the Data Platform team of an EU-based Client – a logistics company specializing in on-demand urban delivery solutions. The platform connects businesses of all sizes with a network of independent couriers to provide fast, flexible last-mile delivery, ranging from instant deliveries (often within an hour) to scheduled services. 

Operating across multiple countries in Europe, they support industries such as retail, grocery, e-commerce, and restaurants. The company’s mission is to make urban logistics faster, more efficient, and more sustainable by leveraging a multi-modal courier fleet, including bikes and electric vehicles. 

This role is ideal for a hands-on engineer who enjoys building robust data systems and enabling teams to work effectively with data at scale. 

Experience / Skills required: 

Must have: 

• 3+ years of experience as a Data Engineer 
• Strong programming skills in Python 
• Solid experience writing and optimizing SQL queries 
• Hands-on experience with dbt Core for data transformation 
• Deploy and maintain scalable data infrastructure on Kubernetes, including managing open-source tools like Airflow, dbt, and Superset on AWS
• Familiarity with AWS data ecosystem, including: S3, Redshift, Glue
• Experience building or maintaining data pipelines and ETL/ELT processes 
• Experience working with Kafka or Kafka Connect for streaming data pipelines 
• Familiarity with Kubernetes environments 
• Excellent English communication and presentation skills 

Nice to have: 

• Experience implementing CI/CD workflows with GitHub Actions 
• Exposure to Apache Spark for large-scale data processing 
• Experience working in data-driven product companies or logistics platforms 

Responsibilities: 

• Design, implement, and maintain a robust Data Platform that collects, stores, and processes data, focusing on scalability and reliability
• Work closely with Analytics Engineers, Data Analysts, and Software Engineers to develop self-serve data solutions for ingestion, transformation, visualization, and data protection, ensuring scalability to meet user needs
• Employ DataOps practices to enhance data quality, governance, and operational efficiency across the platform
• Utilize pair programming, code reviews, and workshops to share knowledge about Python, code architecture, tooling, integration, and deployment, fostering team collaboration
• Monitor and optimize data pipelines for performance and reliability, ensuring seamless data flow across the platform

We offer:  

• Competitive salary with the regular review 
• Vacation (up to 20 working days) 
• Sick leaves (10 working days) 
• National Holidays as a time off (11 days) 
• Online English courses 
• Accountant assistance and legal support 
• Flexible working schedule, remote format  
• Direct cooperation with the customer 
• Dynamic environment with low level of bureaucracy and great team spirit 
• Challenging projects in diverse business domains and a variety of tech stacks 
• Communication with Top/Senior level specialists to strengthen your hard skills 
• Online teambuildings 
• Volunteering culture development and support