RH
Data Engineer IV
Robert Half
Philadelphia · Hybrid Senior 1w ago
About the role
Senior Data Engineer
Location: Philadelphia, PA (Hybrid/Onsite as required)
Employment Type: 39 Week Contract, Potential for Extension
Project Focus: Salesforce → Databricks Data Migration
About the Role
We 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 Responsibilities
Data 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
- Spark and PySpark for all high‑volume processing and transformation work (must‑have).
Responsibilities
- 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).
- 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.
- 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.
Skills
AWSConcourseDatabricksETLGitHub ActionsMulesoftPythonSalesforceSparkSQLTerraform
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