Lead Data Engineer

We are looking for a Lead Data Engineer to drive the unification, governance, and scalability of our data platform. This role is critical in shaping how data is stored, modeled, and delivered across the company. You will lead the standardization of processes, bring in modern technologies such as DBT, and build a high-performing Data Engineering culture that supports product, marketing, and analytics teams.

For which tasks (responsibilities)?

• Own the design and evolution of data architecture, ensuring scalability and reliability

• Standardize processes across data engineering workflows and establish a strong DE culture

• Lead integration and adoption of DBT

• Optimize DWH for performance, cost efficiency, and sustainability

• Oversee end-to-end ETL/ELT pipelines, ensuring monitoring, quality, and documentation

• Improve integration speed with external services (MMP, Adapty, etc.)

• Migrate orchestration workflows to Airflow and optimize pipelines

• Drive data quality management, lineage, and documentation of entities and marts

• Define long-term templates and best practices for the data platform

• Build and scale a team of Data Engineers, setting goals and supporting professional growth

• Collaborate closely with Analytics, Marketing, and Development teams to enhance and support the data model

What kind of professional are we looking for?

• 5+ years of experience in Data Engineering, with at least 2+ years in a Lead or Senior role managing a team

• Strong hands-on expertise with GCP (BigQuery), DBT, Airflow, SQL optimization, and Python

• Proven experience designing, optimizing, and maintaining large-scale DWH solutions

• Understanding and practical experience with streaming technologies (Kafka, RabbitMQ preferred)

• Solid background in building and scaling data pipelines with a focus on reliability, performance, and cost optimization

• Experience collaborating with cross-functional stakeholders (Analytics, Marketing, Development)

Soft Skills

• Integrity and ownership mindset

• Autonomy and ability to drive projects end-to-end

• Systems thinking and structured problem-solving

• Adaptability in fast-paced and changing environments

• Proactive and initiative-driven approach

• Strong leadership and mentoring abilities

Why do we enjoy working here?

• Leadership with real impact – Shape data architecture and strategy, with direct influence on business growth

• Freedom to innovate – Work with modern tools and approaches (cloud platforms, orchestrators, streaming) without being constrained by legacy systems

• Challenging, industry-level growth – Tackle complex problems in big data, machine learning pipelines, and real-world system scaling, strengthening your expertise and reputation

• Influence on the team – Build a high-performing Data Engineering team, set standards, and mentor engineers

• Flexibility and balance – Hybrid or remote work options, with a focus on results rather than micromanagement

What are the conditions and bonuses?

• Highly competitive compensation package that recognizes your expertise and experience level

• Performance Review practice to exchange feedback and discuss terms of cooperation

• Flexible schedule, opportunity to work in a stylish and comfortable office or remotely

• Respect for work-life balance (holidays, sick days)

• Bright corporate events and gifts for employees

• Additional medical insurance

• Compensation for specialized training and conference attendance

• Restaurant lunches covered by the company for office employees, plus year-round access to endless delicious snacks