🌍Remote work: fully remote.

📑Assignment type: B2B.

📕Project language: English.

⏳Project length: > 12 months + prolongations.

⏰Start: ASAP / 1 month.

💻Workload: full time.

⚙️Recruitment process: 2 interviews with the client.

💼 Industry: IT Services / Digital Consulting

🔍Additional information: After receiving the offer, a background check is carried out (references, criminal record check, etc.).

Summary: The primary purpose of the Data Engineer / DataOps Engineer role is to develop and manage data pipelines and workflows, enhancing the organization's data platform capabilities. This position is crucial for ensuring that data is processed reliably and efficiently, enabling better decision-making across the company.

5+ years of professional practice in data engineering.

Strong, practical experience with Snowflake (views, tables, performance tuning, orchestrated ELT processes).

Solid expertise using dbt for SQL-based transformations.

Hands-on experience with Airflow for workflow scheduling and automation.

Experience deploying and maintaining containerized workloads on Kubernetes.

Familiarity with cloud environments, with strong understanding of Microsoft Azure services.

Practical experience building ETL/ELT pipelines and maintaining production data workflows.

Good understanding of Git-based development, CI/CD pipelines, and general DevOps principles.

Analytical mindset and ability to troubleshoot issues in complex systems.

Data Engineer / DataOps Engineer

📝 Opis główny / Wstęp

📡 Metadata statystyk