Mid/Senior Data Engineer

We are looking for an experienced Data Engineer who goes beyond simply delivering tickets and is ready to step into the role of a Technology Partner. This position is designed for someone who can take ownership of a greenfield data platform, design the architecture from scratch, select the right technology stack, and actively advise business stakeholders on the best possible solutions.

The role combines hands-on engineering with consulting and advisory responsibilities. You will work closely with business and technical stakeholders, translating business goals into scalable, secure, and cost-effective data solutions.

We offer:

Budget: up to 120-160 PLN (mid/senior level)

Project duration: ~3 months with a strong option for extension (long-term collaboration mindset)

Start date: ASAP, no later than 01.02.2026

Availability: minimum 4h overlap between 15:00–19:00 CET (collaboration with USA/UK teams)

Tasks:

• Architecture & Strategy: Design scalable, greenfield data architectures and select the most suitable technologies (e.g. Snowflake vs BigQuery, Airflow vs Prefect) based on real business needs.

• Consulting & Advisory: Translate business objectives into technical solutions and proactively challenge suboptimal ideas by proposing better tools and approaches.

• Data Pipelines: Build and maintain efficient ETL/ELT pipelines and data lakes using a modern data stack.

• Security & Compliance: Design solutions following a security-by-design approach, including GDPR/RODO compliance, data masking, role-based access control, and encryption.

• Business Collaboration: Work directly with stakeholders to define analytical requirements and deliver dashboards that support management and executive decision-making.

• Proactive Optimization: Monitor performance and costs, identifying and implementing improvements before issues impact the platform or the business.

Requirements

• Strong expertise in designing and implementing Modern Data Stack platforms (e.g. Snowflake, BigQuery, Redshift, dbt, AI-driven components), with the ability to clearly justify architectural and tooling decisions.

• Very good knowledge of SQL and Python, along with hands-on experience using orchestration tools such as Airflow or Prefect.

• Practical experience with cloud platforms (AWS, GCP, or Azure) and managed data processing services.

• Solid understanding of data security and governance, including access management, encryption, regulatory compliance, and data protection best practices.

• Experience in data modeling for BI and reporting tools such as Power BI, Tableau, or similar platforms.

• Excellent English communication skills (minimum C1), enabling you to run technical workshops and explain complex architectures to non-technical stakeholders.

• A strong consulting mindset with the ability to challenge business requirements and propose higher-ROI solutions.

• Ownership-driven attitude: preference for building systems from scratch and taking responsibility for the entire data lifecycle.

• High level of proactivity, with the ability to identify problems and improvement opportunities without waiting for formal requests.

Nice to have

• Experience with data platform migrations (legacy systems to modern data stacks).

• Familiarity with data quality, monitoring, and observability tools.