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Data Engineer Snowflake

Summary

Senior Data Engineer builds and optimizes Snowflake-based pipelines and data models for an international e-commerce platform, enabling analytics and BI across the business.

Data Engineer (Snowflake Expert)

Project: E-commerce
Location: Remote (with occasional meetings if required)
Start: ASAP
Contract: B2B
Seniority: Senior
Language: English

About the role

We are looking for a Senior Data Engineer with strong Snowflake expertise to join an international e-commerce project. You will become part of a data engineering team responsible for building and maintaining modern cloud-based data platforms that support analytics, business intelligence, and data-driven decision-making across the organization.

This role is ideal for someone who enjoys designing scalable data solutions, optimizing data pipelines, and working closely with analytics and business teams in a fast-paced environment.

Your responsibilities

  • Design, develop, and maintain scalable data pipelines using Snowflake.

  • Build and optimize ELT/ETL processes for large volumes of business data.

  • Develop robust data models supporting reporting and analytics.

  • Optimize Snowflake performance, storage, and compute costs.

  • Integrate data from multiple internal and external sources.

  • Ensure data quality, reliability, and governance across the platform.

  • Collaborate with Data Analysts, Data Scientists, Product Owners, and business stakeholders.

  • Implement monitoring, testing, and automation for data workflows.

  • Participate in architecture discussions and contribute to continuous platform improvements.

Requirements

  • 5+ years of experience as a Data Engineer.

  • Strong commercial experience with Snowflake.

  • Excellent SQL skills.

  • Experience building cloud-based data platforms (AWS, Azure, or GCP).

  • Hands-on experience with Python for data engineering.

  • Experience with ETL/ELT development.

  • Knowledge of modern orchestration tools such as Airflow or similar.

  • Experience working with large-scale datasets.

  • Understanding of data warehousing concepts and dimensional modeling.

  • Experience with Git and CI/CD practices.

  • Strong communication skills and the ability to work in an international environment.

  • Professional level of English.

Nice to have

  • Experience in the e-commerce or retail industry.

  • Knowledge of dbt.

  • Experience with Kafka or other streaming technologies.

  • Familiarity with Terraform or Infrastructure as Code.

  • Experience with containerization (Docker, Kubernetes).

  • Exposure to BI platforms such as Power BI or Looker.

See also