Data Engineer – Salesforce & Databricks

About the role

We are looking for a Data Engineer with strong expertise in Salesforce Data Cloud and Databricks to design, build and maintain data pipelines that support real‑time decisioning and analytics across our enterprise environment.

Key responsibilities

• Build and manage DMOs, DSOs, and source‑to‑model mappings in Salesforce Data Cloud.
• Develop data integration and offload solutions with upstream and downstream systems, including identity resolution and unified customer profiles.
• Design, implement and maintain batch and streaming pipelines on Databricks, ingesting data from CRM, digital and third‑party sources.
• Support deployments across Dev, SIT, UAT, Pre‑Prod and Production environments, handling data onboarding, validation and documentation.
• Collaborate with DevOps, architects and operations teams to ensure platform reliability and performance.
• Provide data requirements for real‑time decisioning platforms such as Pega, and partner with analytics teams for timely data delivery.
• Deliver use cases in Agile squads, manage cross‑team dependencies and maintain technical documentation, runbooks and implementation plans.

Required profile

• 3‑5+ years of enterprise data engineering experience.
• Hands‑on experience with Salesforce Data Cloud (DMOs, DSOs, Data Streams, Identity Resolution).
• Strong knowledge of Databricks, data lakes, ETL/ELT and pipeline orchestration.
• Proficiency in SQL and Python.
• Experience with release management, deployment processes and technical documentation.

Required skills

• Salesforce Data Cloud
• Databricks
• SQL
• Python
• Pega (or equivalent real‑time decisioning platform)
• AWS S3
• Azure Data Lake
• Airflow or equivalent workflow orchestration tool