Senior Snowflake Engineer

Accountabilities:

• • Design, develop, maintain, and optimize scalable ETL/ELT pipelines using Matillion.
  • Build and enhance cloud-based data warehouse solutions using Snowflake.
  • Develop robust data processing frameworks, automation scripts, and supporting tools with Python.
  • Create and maintain data models, transformations, and workflows that support analytics and business intelligence requirements.
  • Optimize Snowflake environments through query tuning, clustering strategies, warehouse management, and other performance optimization techniques.
  • Integrate data from multiple structured and unstructured sources while ensuring reliable and efficient data movement.
  • Implement data quality checks, validation processes, monitoring, alerting, and error-handling mechanisms.
  • Collaborate with business stakeholders, analysts, and cross-functional engineering teams to understand requirements and deliver high-quality data solutions.
  • Participate in code reviews, testing, deployments, and production support activities.
  • Follow established best practices for data security, governance, documentation, and engineering quality.
  • Contribute to continuous improvement of data pipelines, workflows, development processes, and cloud data infrastructure.
  • Support the adoption of modern data engineering practices, including orchestration, automation, and CI/CD where applicable.

  Requirements:

  • 4–8 years of professional experience in data engineering or a closely related field.
  • Strong hands-on experience with Python, Matillion, and Snowflake.
  • Proven experience designing and developing ETL/ELT pipelines and data integration solutions.
  • Strong SQL skills, including experience with query optimization and performance tuning.
  • Solid understanding of data warehousing principles, architecture, and dimensional data modeling.
  • Experience working with at least one major cloud platform, such as AWS, Azure, or GCP.
  • Familiarity with Git, CI/CD pipelines, and Agile development methodologies.
  • Strong analytical, troubleshooting, and problem-solving capabilities.
  • Ability to work collaboratively with technical and non-technical stakeholders while also taking ownership of individual deliverables.
  • Strong attention to data quality, reliability, security, and maintainability.
  • Experience with data orchestration tools such as Airflow is an advantage.
  • Exposure to dbt is desirable.
  • Knowledge of REST APIs and modern data integration techniques is a plus.
  • Familiarity with data governance, security, and compliance best practices is preferred.
  • Strong communication skills and the ability to operate effectively in a fast-paced, collaborative environment.

  Benefits:

  • Opportunity to work on modern cloud-based data engineering and analytics solutions.
  • Hands-on experience with Snowflake, Matillion, Python, and other leading data technologies.
  • Exposure to large-scale data integration, data modeling, automation, and performance optimization challenges.
  • Collaborative environment involving data engineers, analysts, business stakeholders, and cross-functional technology teams.
  • Opportunities to work with major cloud platforms and modern data engineering practices.
  • Professional growth through exposure to emerging tools, technologies, and complex data projects.
  • Agile working environment focused on innovation, continuous improvement, and high-quality delivery.
  • Competitive compensation and benefits, subject to local employment terms.
  • Opportunity to contribute to data solutions that create measurable business value.