Senior Data Engineer

Technologies we use

About the project

This is how we organize our work

Team size

This is how we work

Your responsibilities

• Designing and implementing scalable, production-grade data pipelines, data models, and data processing frameworks in cloud environments.
• Leading the technical design of cloud data architectures, contributing to standards, guidelines, and long-term platform strategy.
• Driving best practices in data engineering: quality assurance, lineage, observability, testing, automation, documentation.
• Optimizing data workflows for performance, cost efficiency, and reliability across distributed systems.
• Collaborating closely with clients and senior stakeholders to understand requirements, propose solutions, and communicate technical decisions.
• Working with CI/CD pipelines, infrastructure-as-code, and automation (DataOps) to streamline deployments and operations.
• Integrating data solutions with BI, ML, and application layers across diverse client environments.
• Mentoring mid-level engineers, supporting them in technical growth (without formal line management).
• Staying up-to-date with emerging technologies and proposing innovations to enhance platform capabilities.

Our requirements

• 4+ years of hands-on experience as a Data Engineer or in a closely related engineering role.
• 2+ years experience working with cloud platforms - we operate primarily in Azure, but AWS/GCP experience is equally valuable.
• Strong Python skills - ability to write maintainable, production-ready code in distributed data environments.
• Advanced SQL proficiency and experience with relational databases (SQL Server, PostgreSQL, etc.).
• Expertise in DWH data modeling, ETL/ELT architectures, and modern data design patterns (Lakehouse preferred).
• Solid understanding of cloud architecture, networking fundamentals, security, APIs, and scalable systems.
• Experience working with large-scale, high-volume datasets.
• Strong ownership mindset, creativity, and openness to innovation.
• Ability to operate autonomously and drive initiatives in dynamic, evolving cloud projects.

Optional

• Experience with Databricks, Apache Spark, PySpark (big advantage).
• Hands-on knowledge of Apache Airflow or other orchestration tools.
• Experience with Azure DevOps or GitHub Actions for CI/CD.
• Familiarity with infrastructure as code (Terraform/Bicep).
• Exposure to AI/ML pipelines or MLOps environments.

What we offer

• Professional Growth:
• Access to top e‑learning platforms and development budget
• Real ownership opportunities - expand your scope, drive solutions, lead initiatives; most of our Leads are promoted internally
• Work Environment:
• Long-term collaboration via B2B - we value lasting partnerships
• Remote-first
• Flexible hours
• Work alongside exceptional engineers and experts
• Flat structure where every person matters and influences the company
• Culture & Integration:
• Full-company integration trips (including international ones)
• Team-level integration budgets
• Open, supportive, and collaborative culture

This is how we work on a project

EQUAL OPPORTUNITY