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We are seeking a Senior Data Engineer to support a high-impact Salesforce initiative focused on large-scale data migration and pipeline development into Databricks for a major advertising platform. This long-term remote contract role centers on building and optimizing ETL pipelines using Python, Spark, and PySpark within an AWS environment, enabling seamless data integration between Salesforce and modern data platforms. The position collaborates closely with cross-functional engineering teams to deliver scalable, reliable data solutions, improve deployment processes through CI/CD and infrastructure-as-code practices, and ensure the overall quality, performance, and resilience of critical data systems.
Job Responsibility
Develop ETL pipelines to migrate and integrate data into Databricks
Support Salesforce to Databricks data migration and integration
Design, build, test, and maintain data pipelines on AWS + Databricks
Translate business requirements into scalable data engineering solutions
Contribute to data warehousing components for Salesforce Phase 2
Utilize Terraform for infrastructure provisioning and management
Implement and maintain CI/CD pipelines (Concourse or GitHub Actions)
Perform testing, QA, and documentation for all data engineering work
Provide post-deployment support and troubleshooting
Identify and mitigate risks, including single points of failure (SPOF)
Collaborate within Agile teams and participate in weekly Scrum ceremonies
Work closely with senior engineers and contribute to best practices and knowledge sharing
Requirements
7–9 years of experience in data engineering / data integration projects