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.

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