Senior Data Engineer (with Snowflake)

We are seeking a highly skilled Snowflake Data Engineer to design, develop, and manage our cloud-based data infrastructure using Snowflake. The ideal candidate will have deep experience in data warehousing, ETL/ELT development, and cloud data platform architecture, with a strong focus on performance, scalability, and reliability.

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Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field
• 3+ years of background in data engineering or data platform development
• Hands-on experience with Snowflake, including performance tuning, data modeling, and advanced SQL
• Proficiency in SQL and scripting languages such as Python or Scala
• Competency in ETL/ELT frameworks and orchestration tools (e.g., dbt, Airflow, Talend)
• Knowledge of cloud platforms such as AWS, Azure, or GCP
• Understanding of data warehousing concepts, star/snowflake schema design, and normalization/denormalization techniques
• Practice in agile development environments and using tools like Jira or Confluence

Nice to have

• Snowflake certification (e.g., SnowPro Core/Advanced)
• Experience with data governance and privacy frameworks (GDPR, HIPAA, etc.)
• Exposure to machine learning pipelines and streaming data (Kafka, Kinesis)
• Familiarity with CI/CD pipelines, Git, and infrastructure-as-code tools like Terraform

English level

Upper-Intermediate

Responsibilities

• Design, implement, and optimize data pipelines in Snowflake to support business intelligence, analytics, and data science needs
• Develop and manage scalable ELT/ETL workflows using tools like dbt, Apache Airflow, Matillion, or similar
• Model and maintain data warehouses/data lakes, ensuring best practices in dimensional modeling and data partitioning
• Create and maintain secure and governed data environments, enforcing data access policies and roles
• Monitor data pipelines for performance, reliability, and cost-efficiency
• Collaborate with data analysts, data scientists, and other engineering teams to understand data needs and deliver solutions
• Integrate Snowflake with external data sources and tools such as AWS S3, Azure Data Lake, Kafka, or third-party APIs
• Troubleshoot and resolve data issues, ensuring data quality and consistency across platforms
• Automate and maintain CI/CD pipelines for data infrastructure deployments
• Stay up to date with Snowflake features and industry best practices