Principal Data Consultant

Summary

Designs and implements cloud-based data platforms and architectures for analytics and reporting, using SQL, Python, Spark, and GCP tools in Łódź, Poland.

Type of contract: B2B contract

Salary range: 200-265 PLN/H

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.

Your tasks

  • Design and develope data pipelines in both batch and streaming models
  • 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
  • Participating in the migration of solutions from on-premise environments to Google Cloud
  • Data modeling and collaboration with data architects
  • Automating data processing workflows and implementing DataOps best practices
  • Optimizing the performance and costs of solutions running in cloud environments

Your skills

  • 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 within GCP
  • Kowledge of BigQuery and designing analytical and data warehousing solutions
  • Experience with Apache Beam and Dataflow (batch and streaming)

Nice to have

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