Principal Data Engineer

• At least 8 years of commercial experience as a Data Engineer, Lead Data Engineer, or Data Architect
• Strong expertise in SQL
• Strong expertise in Python
• Strong expertise in Spark or PySpark
• Experience in data architecture, data quality, metadata management, analytics, and reporting
• Strong experience with cloud data engineering tools, preferably within GCP
• Experience designing data architectures on Databricks and/or Snowflake platforms
• Experience with modern data engineering toolsets

Nice to have

• Experience with BI tools such as Power BI, Qlik, or Apache Superset
• Experience in consulting environments
• Experience in Data Science

We are GFT Poland. WE KNOW how to tackle complex issues with innovative approach to deliver the highest value. Our reputation has been built around one simple rule: we do not overpromise, WE DELIVER . We deliver to our employees, clients and partners. WE GROW as you grow, so investing in you is our business strategy. Caring for each other is our priority. WE CARE who you are, what you need, how you feel. WE CARE to smile, have fun and develop as human beings.

What will you do?

Join a team focused on designing and delivering modern data platforms and architectures that support advanced analytics, reporting, and data-driven decision-making. You will work closely with business stakeholders and engineering teams to define data strategies, shape architectural solutions, and ensure high standards of data quality, scalability, and performance across cloud-based environments. Why Choose GFT?

• A culture of top performance
• Deep tech IT engineering & consulting
• 1200 skilled & top-class experts
• 77% of the team are regular/senior
• Products that contribute to a sustainable world
• Competitive salary and benefits
• Ambitious projects, trainings and tools you need to flourish
• Google Cloud Partner of the Year - for going above and beyond for customers

,[Design and optimize data platform architecture, Design and implement data processing frameworks, templates, and solutions, Collaborate closely with business stakeholders and engineering teams, Review, refine, and translate business requirements into architectural decisions, Drive data quality, metadata management, and governance best practices, Support the adoption of modern cloud-based data engineering solutions] Requirements: Spark, Cloud, Data engineering, SQL, Python, GCP, BI, Power BI, Qlik, Data science, Apache Superset Additionally: International projects, Sport subscription, Training budget, Private healthcare, Platforma szkoleniowa, Free coffee, Playroom, Free beverages, Modern office, Bike parking, Free parking, In-house trainings.