Description Senior Data EngineerLocation: Philadelphia, PA (Hybrid/Onsite as required)
Employment Type: 39 Week Contract, Potential for Extension
Project Focus: Salesforce ? Databricks Data Migration
About the RoleWe are seeking a
Senior Data Engineer to support a major Salesforce data migration initiative. This role is centered around building, optimizing, and maintaining high-quality data pipelines that feed into Databricks, with a strong emphasis on Spark/PySpark and Python-based ETL development. The engineer will work closely with a senior team member, participate in Agile ceremonies, and contribute to the development of a core CRM data platform.
Key ResponsibilitiesData Engineering & Development- Develop ETL jobs and data pipelines that migrate and integrate data between Salesforce, AWS, and Databricks.
- Build, test, and maintain scalable data pipelines on AWS + Databricks environments.
- Use Python as a primary language for data engineering tasks and ETL job creation.
- Utilize Spark and PySpark for all high-volume processing and transformation work (must-have).
- Support integration and pipeline development, including Mulesoft-related components.
- Conduct documentation, testing, QA, and post-delivery support for all data engineering outputs.
- Identify and mitigate risks, including eliminating single points of failure (SPOFs).
Infrastructure & DevOps Collaboration- Use Terraform for infrastructure provisioning and environment management.
- Set up and manage CI/CD pipelines using Concourse or GitHub Actions to ensure consistent and reliable deployments.
- Troubleshoot pipeline issues, resolve defects efficiently, and maintain reliable operations.
Cross-Team Collaboration- Partner with engineering, architecture, and technical product teams to translate requirements into scalable data solutions.
- Contribute to best practices, knowledge-sharing, and continuous improvement across the engineering organization.
- Participate in weekly Scrum ceremonies and collaborate in an Agile environment.
Requirements QualificationsRequired- Bachelor's degree in Computer Science or related Engineering field.
- 7-9 years of hands-on experience with data engineering and data integration projects.
- Strong proficiency in Python, including building ETL jobs.
- Spark and PySpark expertise required (core skillset).
- Experience building pipelines into Databricks.
- Hands-on experience with AWS services (e.g., EC2, S3, RDS, DynamoDB, Lambda, API Gateway, Fargate).
- Proven track record developing cloud-based services, SaaS solutions, or platform-level architectures.
- Strong understanding of distributed systems, scalability, and performance optimization.
- Experience working in Agile development environments.
Preferred- Java (nice to have, not required).
- Salesforce data structure familiarity (nice to have).
- Experience developing microservices and working with modern CI/CD architectures.
- Familiarity with Linux-based environments, containerization, and DevOps tooling.
- Understanding of data persistence solutions, both relational and NoSQL.
- Master's degree in Computer Science or related field (optional, not required).
- Prior experience establishing platform security, monitoring, and reliability best practices.
Additional Information- Candidates will work closely with a senior engineer.
- This role has a strong emphasis on data pipeline creation for CRM systems.
- The engineer will contribute to a large-scale, high-visibility migration initiative.
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