Data Engineer Location: Fully remote (based in Poland) Type: B2B contract Salary: Up to 27 000 PLN (B2B) + paid holidays Our ClientOur client is a leader in the SaaS industry, specializing in innovative software solutions for insurance companies. With over 20 years of experience, they deliver a comprehensive suite that supports key insurance operations, including policies, claims, reinsurance, and payments.Currently undergoing a major technological transformation, the company is establishing a Competence Center in Warsaw and transitioning towards a Cloud Native, multi-tenant platform to modernize its infrastructure. This strategic investment in cloud services aims to create a scalable, efficient, and future-ready system.Job SummaryAs a Data Engineer, you’ll play a key role in collecting, integrating, and analyzing data across multiple software engineering tools. You’ll build actionable reports, detect anomalies, and partner closely with engineering leaders to drive data-informed improvements in engineering processes.Key ResponsibilitiesData Collection & Integration Aggregate data from diverse engineering tools (CI/CD pipelines, code repositories, issue trackers, observability platforms). Integrate and manage data within Snowflake for scalable analytics and reporting. Design and maintain Azure Data Factory pipelines for data ingestion and transformation. Ensure data accuracy and consistency across all sources. Reporting & Visualization Build dashboards and reports in Power BI or Tableau to monitor engineering health metrics (velocity, quality, reliability). Generate periodic and ad-hoc reports for leadership review. Anomaly Detection & Analysis Identify trends, anomalies, and outliers in engineering performance data. Conduct root cause analyses and collaborate with engineering teams to resolve issues. Stakeholder Engagement Partner with software engineering leaders to interpret insights and recommend actions.

Communicate findings clearly to both technical and non-technical audiences.

Required Skills & Experience Snowflake expertise for data warehousing, query optimization, and analytics. Hands-on experience with Azure Data Factory for ETL and orchestration. Strong proficiency in SQL for data manipulation and analysis. Familiarity with software engineering lifecycle tools (GitHub, Jenkins, Jira, SonarQube). Understanding of CI/CD processes and modern DevOps practices. Solid understanding of the software development lifecycle (SDLC).

Excellent communication and collaboration skills.

Preferred Qualifications Proficiency in Python or C# for automation and data workflows. Experience with anomaly detection techniques and statistical analysis. Knowledge of cloud platforms (Azure, AWS) and infrastructure monitoring. Understanding of the business of engineering.

Ability to work independently and manage multiple priorities.