Data Engineering
usource
Job Description
- Analyze and develop a deep understanding of existing Snowflake data models, ETL/ELT processes, Salesforce Data Cloud structures, and enterprise integrations.
- Support Redshift-to-Snowflake migration initiatives, including assessment, architecture planning, schema conversion, data migration, testing, performance tuning, and production deployment.
- Design, develop, and maintain Snowflake database objects including tables, views, streams, tasks, stored procedures, and data pipelines.
- Build and manage Salesforce Data Cloud (Data 360) components including:
- Data Streams
- Data Lake Objects (DLOs)
- Data Model Objects (DMOs)
- Identity Resolution
- Calculated Insights
- Customer 360 Profiles
- Develop scalable ETL/ELT pipelines supporting enterprise reporting and analytics initiatives.
- Create and optimize complex SQL queries for reporting, transformation, reconciliation, and analytical workloads.
- Design and support integrations between:
- Snowflake
- Salesforce Data Cloud
- Salesforce CRM
- AWS Services
- Enterprise Applications
- Validate data migrations, data loads, and transformations to ensure completeness, consistency, and accuracy.
- Monitor and optimize Snowflake performance, including:
- Query tuning
- Warehouse sizing
- Workload management
- Storage optimization
- Support User Acceptance Testing (UAT), release activities, and post-production support.
- Troubleshoot and resolve production incidents, data discrepancies, and integration failures.
- Develop technical documentation for data models, mappings, ETL workflows, integrations, and operational procedures.
- Implement data governance, security, compliance, and privacy controls.
- Collaborate with business stakeholders and technical teams to deliver scalable Customer 360 and analytics solutions.
- Ensure adherence to SLAs, operational standards, and enterprise best practices.