Data Engineer

What you will do

• Design and implement robust, scalable data pipelines using Snowflake and modern ETL/ELT frameworks.
• Collaborate with data architects, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.
• Optimize Snowflake performance through clustering, partitioning, and query tuning.
• Develop and maintain data models (star/snowflake schemas) and data marts for enterprise reporting.
• Integrate data from diverse sources including APIs, cloud storage (AWS/GCP/Azure), and on-prem systems.
• Ensure data quality, security, and governance through automated validation, masking, and role-based access controls.
• Support CI/CD workflows and infrastructure-as-code practices using tools like Git

About you

Skills and Qualifications
 

• Technology/Tools:  Sigma*, Snowflake (Datawarehouse), Azure, integrations etc.,
• Hands on experience with Snowflake modeling including but not limited to roles, databases, schemas, Store Procedures, UDf’s, snowpipe, shares and streams etc.
• Extensive knowledge of SQL, Python
• Hands on experience with SQL performance measuring, query tuning and database tuning
• Develop Snowflake Integration with third-party tools and able to manage and maintain pipelines
• Experience with Azure or other cloud platforms
• Bachelor’s or Master’s degree in Computer Science, Information Systems, or related field.
• 5–7 years of experience in data engineering, with at least 3 years working with Snowflake.
• Strong proficiency in SQL and Python for data transformation and automation.
• Hands-on experience with cloud platforms (AWS preferred)
• Familiarity with data warehousing concepts, dimensional modeling, and performance optimization.
• Experience with version control, DevOps practices, and Agile methodologies.