Data Integration Engineer Snowflake

Responsibilities
Design and develop scalable data integration solutions with a primary focus on Snowflake, leveraging AWS Glue, Azure Data Factory (ADF), or Google Cloud Dataflow.
Implement ETL/ELT pipelines optimized for Snowflake, ensuring efficient data ingestion, transformation, and storage in multi-cloud environments.
Ensure adherence to data governance, security, and compliance best practices for Snowflake implementations.
Automate data workflows and infrastructure deployment using Terraform, Bicep, CloudFormation, and Deployment Manager.
Develop and manage real-time and batch data processing architectures, integrating Kafka, AWS Kinesis, Azure Event Hub, and Google Pub/Sub with Snowflake.
Optimize Snowflake performance, including query tuning, clustering, and cost optimization strategies.
Implement monitoring and observability using tools like Snowflake Query Profiler, CloudWatch, Azure Monitor, Google Cloud Operations Suite, and Datadog to ensure data integrity and system reliability.
Collaborate with data engineers, architects, and business teams to align Snowflake-based solutions with business objectives.
Troubleshoot and resolve data integration and performance issues within Snowflake, ensuring high availability and scalability.
 

Qualifications
Expertise in Snowflake, with a deep understanding of data warehousing, query optimization, and performance tuning.
Strong experience with AWS, Azure, and Google Cloud, leveraging serverless data processing and data lake architectures.
Proficiency in SQL, Python, and Scala, with hands-on experience in Apache Spark, Databricks, and Airflow for data orchestration.
Solid background in data modeling, ETL/ELT pipeline optimization, and data governance best practices.
Experience with CI/CD for data deployments, utilizing GitHub Actions, Azure DevOps, AWS CodePipeline, and Cloud Build.
Familiarity with data security, encryption, and compliance frameworks (GDPR, HIPAA, SOC 2).
Self-starter with the ability to lead Snowflake-driven initiatives, optimize cost efficiency, and drive best practices in cloud data engineering.
Strong consulting and communication skills, collaborating effectively with engineering, operations, and business teams to align data strategies with business objectives.