Snowflake Data engineer with 5 years of experience

About the role

We are looking for a Snowflake Data Engineer to build reliable data pipelines and make data accessible for analytics and reporting. You will work with analysts, engineers, and business teams to bring data from multiple sources into Snowflake, improve data quality, and develop well-structured data models.

Responsibilities

Design, build, and maintain data pipelines that load and transform data in Snowflake.

Develop data models and reusable datasets for reporting and analytics.

Write and optimize SQL queries, stored procedures, and transformation workflows.

Integrate data from APIs, databases, files, and cloud storage.

Monitor pipelines, investigate failures, and resolve data quality issues.

Improve Snowflake performance and manage compute costs.

Document data flows, definitions, and engineering processes.

Work with stakeholders to turn reporting requirements into dependable data solutions.

Around 5 years of data engineering experience, including hands-on work with Snowflake.

Strong SQL and Python skills.

Experience building ETL or ELT pipelines and working with large datasets.

Familiarity with data modeling, orchestration tools, and Git-based development.

Experience with at least one cloud platform: AWS, Azure, or Google Cloud.

Ability to troubleshoot pipeline failures and communicate clearly with technical and business teams.

Preferred qualifications

Experience with dbt, Airflow, or similar tools.

Knowledge of Snowflake features such as Snowpipe, Streams, Tasks, and role-based access control.

Experience with CI/CD, data quality checks, and warehouse cost optimization.

To apply: Send your resume and a brief description of a Snowflake pipeline or data model you have built to [application email or link].

Experience with dbt, Airflow, or similar tools.

Knowledge of Snowflake features such as Snowpipe, Streams, Tasks, and role-based access control.

Experience with CI/CD, data quality checks, and warehouse cost optimization.