Key Responsibilities
- Design, develop, and maintain scalable data pipelines using Snowflake as the core data warehouse platform.
- Build and optimize batch, file-based, and real-time streaming data ingestion processes from multiple sources.
- Develop data transformation logic using Snowflake SQL, stored procedures, and Python.
- Collaborate with architects, analysts, and business teams to translate requirements into technical solutions.
- Monitor and troubleshoot pipeline performance while ensuring data quality and availability.
- Maintain documentation for data flows, models, and system architecture.
- Partner with DevOps teams to implement CI/CD practices for data pipeline deployments.
Required Skills and Experience
- Bachelor’s degree in Computer Science, Information Systems, or related field.
- 5+ years of experience in data engineering or similar roles.
- 3+ years of strong hands-on experience with Snowflake, including advanced SQL, stored procedures, and performance tuning.
- Experience with data ingestion methods such as bulk loading, micro-batching, and streaming.
- Strong knowledge of AWS services such as S3, Lambda, and CloudWatch, or Azure services including Data Factory, Event Hubs, Blob Storage, and Azure Functions.
- Experience in using Terraform to provision and manage infrastructure, including Snowflake resources or cloud environments.
- Experience working in Azure cloud environments.
- Strong Python programming skills for automation, integrations, and data processing.
- Good experience with SQL Server and relational databases.
- Knowledge of data modeling, security, governance, and best practices.
- Experience with Git and collaborative development environments.
Learn more about this Employer on their Career Site
