Senior Snowflake Data Engineer

Role Description: 12+ years of experience as a Data Engineer. Design, develop, and maintain scalable, resilient data engineering solutions. Strong expertise in Snowflake, Python, PySpark, DBT, Qlik Replicate, and Airflow. Experience building enterprise-grade data pipelines, CDC solutions, and cloud data platforms. Strong understanding of data governance, security, and DevOps practices.

Must-Have: Technical Skills 12+ years of hands-on Data Engineering experience. Deep expertise in Snowflake, including:

• Snowpipe
• TasksStreamsDynamic Tables
• Advanced SQLData Masking PoliciesRBACPerformance tuning
• Strong experience building and maintaining DBT Cloud models with:
• Testing
• DocumentationData lineage
• Excellent proficiency in:
• PythonPySparkExperience developing ingestion frameworks for:
• FilesAPIsSchema validation
• Retry mechanisms
• Metadata capture
• Experience ingesting data from:
• CSVFixed-width files
• Multi-record layoutsJSONXMLExcelSemi-structured data
• Experience designing ingestion patterns for:
• Mainframe VSAMEBCDIC data formats
• Strong expertise in:
• Schema drift detection
• Schema evolution
• Metadata-driven architecture
• Hands-on experience with:
• Qlik Replicate
• Change Data Capture (CDC)
• Full-load database replication
• Experience replicating data from:
• OracleSQL ServerDB2Strong understanding of:
• Data governanceRBACData access controls
• Snowflake security
• Experience implementing:
• Dynamic data masking
• Conditional masking
• Role-based masking
• Experience with Protegrity or similar tokenization/data protection platforms.
• Hands-on experience with:
• Astronomer Airflow
• Workflow orchestration
• Dependency management
• SchedulingRetry logicSLA monitoring
• Experience integrating CI/CD pipelines using:
• GitLabAzure DevOpsStrong knowledge of:
• Git branching strategies
• Merge requests
• Code reviews
• Repository management
• Experience implementing:
• Monitoring
• AlertingPipeline observability
• Expertise in optimizing:
• Snowflake compute
• StorageQuery performance
• Pipeline scalability

Roles & Responsibilities: Design and develop scalable, resilient data pipelines using Snowflake. Build and maintain DBT models with testing, documentation, and lineage. Develop Python/PySpark ingestion frameworks for APIs and file-based integrations. Design ingestion solutions for structured and semi-structured data sources. Implement Mainframe VSAM ingestion for complex EBCDIC data. Detect, analyze, and manage schema drift across multiple data sources. Develop metadata-driven schema evolution strategies. Coordinate schema changes through CI/CD pipelines. Configure and maintain Qlik Replicate for CDC and full-load replication. Build reliable, auditable, and recoverable replication pipelines. Implement Snowflake data masking, RBAC, and governance policies. Apply Protegrity tokenization to protect sensitive data. Build and schedule workflows using Astronomer Airflow. Integrate data pipelines with GitLab and Azure DevOps CI/CD processes. Manage source code repositories and perform code reviews. Implement monitoring and alerting for ingestion, replication, and transformation pipelines. Optimize Snowflake performance, storage utilization, and query execution. Scale data pipelines to support increasing data volumes and low-latency processing.

Generic Managerial Skills: Excellent analytical and problem-solving skills. Strong verbal and written communication skills. Ability to collaborate with cross-functional engineering and business teams. Strong stakeholder management and coordination skills. Ability to lead technical discussions and mentor junior engineers. Experience working in Agile/Scrum environments. Strong ownership, accountability, and commitment to quality delivery. Ability to manage multiple priorities in a fast-paced environment.