We are looking for a Senior Data Engineer:

English Proficiency: Intermediate

Employment type: Full time

Candidate Location: EU

Working Time Zone: CET

Start: ASAP

Planned Work Duration: 6+ months

Customer Description:

The customer is a global mobility and urban services platform offering ride-hailing, intercity travel, delivery, and task assistance services.

Project Description:

The project involves developing scalable, high-performance data pipelines and data infrastructure to support analytics and core business processes.

The role requires deep expertise in Python, SQL, and data architecture with a focus on building reliable data delivery systems.

Project Phase: ongoing

Soft Skills:

• Excellent self-management and ability to work independently

• Proactive ownership-driven mindset

• Clear and effective communication within distributed teams

• Collaborative attitude and openness to feedback

• Strong problem-solving in ambiguous environments

• High attention to detail and code quality

• Adaptability to shifting priorities and new technologies

Hard Skills / Must Have:

• Expert proficiency in Python 3.7+ and SQL (advanced level)

• Deep understanding of multi-layered DWH architecture  (e.g., Raw, ODS/Staging, Data Marts).

• Experience building ETL workflows with workflow orchestrators

• Strong knowledge of OOP, design patterns, and clean architecture

• Experience with major cloud object storage services

• Experience with cloud data warehouse platforms

• Mandatory experience with Git for version control

Hard Skills / Nice to Have:

• Experience with high-load/low-latency systems or message brokers

• Experience with DevOps practices and CI/CD automation tools

• Experience with Infrastructure as Code such as Terraform

• Experience with containerization and orchestration technologies

• Participation in testing and investigation of data quality incidents

Responsibilities and Tasks:

• Design and maintain end-to-end data pipelines (ETL/ELT)

• Build scalable and cost-efficient data infrastructure in the cloud

• Implement monitoring, alerting, and automated validation for data flows

• Participate in data architecture design with focus on resilience and performance

• Optimize existing pipelines and queries for performance and cost efficiency

• Collaborate with analysts to clarify technical requirements

• Conduct root cause analysis for data quality incidents and propose solutions

• Create and maintain technical documentation including schema and lineage

Technology Stack: Python, SQL, DWH architecture, Airflow

Interview stages:

• English check (15 minutes)

• internal technical interview (1-1,5 hour)

• client interview (1 hour)

• client interview – team fit (45 minutes)




📩 Ready to Join?
We look forward to receiving your application and welcoming you to our team!