Informacje o stanowisku

about-project :

• B2B: 1 200 –1 500 zł netto/dziennie
• We are looking for a highly skilled Senior Analytics Engineer to join our data team and drive the design, development, and governance of enterprise-grade data pipelines. In this role, you will work with cutting-edge cloud technologies, collaborate with international stakeholders, and ensure that high-quality, trusted data is available for strategic decision-making across the organization.
• Tech Stack & Environment
• DBT Cloud – core ELT engine
• Snowflake – data warehouse
• AWS S3 – data lake / ingestion zone
• GitHub, Azure DevOps – version control & CI/CD
• Data sources: IQVIA OCE, Salesforce Marketing Cloud, Adobe AEM/Analytics, Shopify, Qualtrics, Accutics, Facebook, LinkedIn, Instagram

• Design, build, and maintain efficient ETL/ELT pipelines in DBT Cloud, ingesting data from sources such as IQVIA OCE, Adobe Analytics, Qualtrics, Salesforce CIAM, and others.
• Contribute to the migration of legacy Snowflake and Qlik environments into the unified EUCAN CDP platform.
• Implement robust data quality validation frameworks (including DBT tests, freshness checks, anomaly detection).
• Support and enhance the RUN Management process: monitoring, job reruns, root cause analysis (RCA), and preventive action implementation.
• Maintain and document model ownership, schema logic, and transformation processes within the CDW_CORE → CDW_STAGE → CDW_PROD architecture.
• Collaborate closely with the Product Owner, Data Architect, and affiliate stakeholders to deliver trusted, scalable, and well-governed data products.
• Mentor junior data engineers and serve as a point of escalation for complex data-related issues.

• 5+ years of experience as a Data Engineer (or similar role) working with cloud-based ELT pipelines.
• Expert-level SQL and DBT data modeling skills.
• Deep understanding of data warehousing concepts: dimensional modeling, incremental loading, performance optimization.
• Hands-on experience with Snowflake and modern cloud data architectures.
• Strong communication and documentation skills – proven ability to work effectively in distributed teams.
• Proactive mindset with ownership over data quality, incident resolution, and disciplined delivery.

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