About the role
We're looking for a Salesforce Data Engineer to build scalable data pipelines and enable seamless data movement between Salesforce and enterprise data platforms. In this role, you'll work on cloud-native data solutions, optimise ETL/ELT workflows, and support analytics by delivering reliable, high-quality data.
Responsibilities:
- Design and develop data pipelines integrating Salesforce with enterprise systems and cloud data platforms.
- Build and optimise ETL/ELT workflows for large-scale data processing.
- Develop data models to support reporting, analytics, and business intelligence.
- Integrate Salesforce using APIs and modern integration frameworks.
- Ensure data quality, governance, security, and performance across data pipelines.
- Collaborate with cross-functional teams to deliver scalable and reliable data solutions.
Requirements:
- 5-10 years of experience in Data Engineering.
- Strong experience with Salesforce data (Sales Cloud and/or Service Cloud).
- Expertise in SQL and programming with Python or Java.
- Hands-on experience with Salesforce APIs, ETL/ELT tools, and cloud platforms (AWS, Azure, or GCP).
- Experience with modern data warehouses such as Snowflake, Databricks, Redshift, BigQuery, or Synapse.
- Familiarity with orchestration tools like Airflow or Azure Data Factory.
- Exposure to CI/CD, Git, and data modelling concepts.
Good to Have
- Salesforce Data Cloud or Marketing Cloud experience.
- Kafka, dbt, Tableau, or Power BI exposure.
- Salesforce or Cloud certifications.