Job Description:
The ideal candidate will be responsible for designing scalable, high-performing data models using Salesforce standard and custom objects. They will implement data modeling strategies including Big Objects for handling large data volumes, ensuring data integrity and consistency using validation rules, automation, and sharing rules. Additionally, they will consolidate data across multiple Salesforce instances for unified views.
The candidate will also develop and manage data pipelines to extract, transform, and load (ETL) Salesforce data into AI/ML platforms, integrate Salesforce data with cloud data lakes or warehouses, and ensure seamless data flow between Salesforce and external systems using APIs, middleware, or ETL tools.
Furthermore, the candidate will collaborate with data scientists and ML engineers to provide clean, structured, and accessible data, support MLOps pipelines by ensuring data availability, versioning, and lineage tracking, and automate data validation, retraining triggers, and rollback mechanisms for ML models.
The candidate must have experience with AWS services like EKS, Lambda, S3, RDS, and EventBridge to support scalable ML operations, implement CI/CD pipelines for data and model deployment using tools like GitHub Actions, and ensure infrastructure security using AWS Secrets Manager, KMS, and VPC configurations.
Additionally, the candidate will define and enforce data governance policies including access control, data quality, and compliance, maintain documentation for data architecture, workflows, and ML infrastructure, and align data architecture with organizational goals and regulatory standards.
Requirements:
• AWS cloud experience is required.
