Data Engineer
Awareson Sp. z o.o.
Data Engineer | 100% Remote | B2B | Up to 165 PLN/h
We are looking for an experienced Data Engineer to join a long-term international project focused on designing, building, and optimizing modern data solutions. In this role, you will work with diverse data sources, develop scalable data pipelines, ensure data quality, and support analytics and AI-driven initiatives.
What we offer
B2B contract
Up to 165 PLN/h
100% remote work
Long-term cooperation in an international environment
Key responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines.
Integrate data from multiple sources, including ERP systems, fund administration platforms, SharePoint, APIs, and flat files.
Build and optimize data models for analytics and reporting.
Implement reconciliation, validation, and data quality processes to ensure accurate and reliable data.
Develop dashboards and support self-service reporting solutions.
Collaborate with business stakeholders to understand data sources, resolve discrepancies, and translate business requirements into technical solutions.
Contribute to data architecture decisions and promote reusable integration and data engineering best practices.
Ensure data security, compliance, and governance standards are followed.
Mentor junior team members and support knowledge sharing within the team.
Requirements
At least 4 years of experience as a Data Engineer or in a similar role.
Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, or a related field.
Strong experience with SQL, Python, and PySpark.
Hands-on experience with Snowflake and/or Databricks.
Experience designing and developing ETL/ELT pipelines.
Experience integrating data from ERP systems, fund administration systems, SharePoint, APIs, and flat files.
Strong understanding of data modeling, dimensional modeling, and query/performance optimization.
Experience implementing data reconciliation, validation, and data quality frameworks.
Familiarity with Sigma or other BI tools such as Power BI or Tableau.
Knowledge of data anonymization, security, compliance, and governance best practices.
Understanding of AI/GenAI data workflows, including preparing high-quality data for LLM-based solutions and applying responsible AI principles.
Excellent communication skills and the ability to collaborate with both technical and non-technical stakeholders.