We are looking for a skilled and proactive Data Engineer Consultant (5+ years of experience) to join our team.
This is not your typical “just give me the specs” type of role. We’re looking for someone with a consulting mindset — someone who’s curious, self-driven, and comfortable working in situations where business needs may be unclear or evolving. You should enjoy digging into problems, asking the right questions, and proposing pragmatic, scalable data solutions — even when the starting point is fuzzy. We’re also looking for someone who’s excited about explaining complex concepts in a simple, approachable way, and who enjoys collaborating with and supporting less experienced team members.
Technology is the heart of everything we do, but we are much more than that.
Enjoy a supportive environment where you can grow, thrive, and work your way.
responsibilities :
Design, build, and maintain scalable data pipelines (ETL/ELT)
Collaborate with business and analytics stakeholders to identify needs and translate them into data solutions
Model and transform data to support analytics, reporting, and machine learning use cases
Work autonomously, organize your own work, and proactively communicate progress and blockers
Drive discussions to clarify business goals and data requirements
Help shape the data engineering culture and best practices in our team
Collaborate with the team, actively supporting others in understanding data engineering concepts and building end-to-end solutions together
requirements-expected :
5+ years of experience in Data Engineering or similar role
Proficiency in SQL and at least one programming language — ideally Python
Experience with cloud-based data platforms (e.g., AWS, GCP, or Azure)
Hands-on experience with modern data stack tools such as:
dbt (data modeling and transformation)
Airflow or similar orchestration tools
Spark or similar distributed data processing tool
Databricks/Snowflake, BigQuery, Redshift, or other cloud data warehouses
Hands-on experience with open source data engineering tools
Experience in distributed data storage architectural design
Familiar with Kubernetes eco-system is nice to have
Familiarity with version control and CI/CD in a data context
Experience with monitoring, testing, and documenting data pipelines
offered :
Co-financed private medical care and MultiSport card
Flexible work setup with self-management, focus time, and offices in great locations in Warsaw and Wroclaw
Knowledge-sharing culture with an internal library, regular learning sessions, and 4 hours/month for self-development
Career growth through an individual path, external workshops, certifications, and our own Tech_hive Entrepreneurship Academy
A people-first atmosphere with weekly breakfasts, mentoring, team retreats, birthday celebrations, and servant leadership culture
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of professional training & courses
