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Generalist data role, metro location, and broad ETL/SQL skillset increase applicant competition.
Core data engineering skills transferable, but Salesforce-specific ETL needs increase domain sensitivity.
No explicit years but specific ETL, SQL and Salesforce data requirements create moderate filtering.
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Design, build, maintain end-to-end ETL pipelines moving data from SQL staging systems to Salesforce with focus on data quality and pipeline reliability.
Optimize and tune ETL logic, SQL queries, and data flow tasks for performance on large, high-volume datasets using techniques like partitioning and incremental loads.
Develop automated workflows for data movement using SSIS or ADF, implement error handling and retry logic, and monitor/fix pipeline failures proactively.
Strong proficiency in SQL including query tuning, stored procedures, and performance optimization.
Experience designing and maintaining data pipelines integrating SQL systems and Salesforce using tools such as SSIS, Airflow, or ADF.
Familiarity with Salesforce Bulk API (v1/v2) and schema mapping for data loading.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in enterprise-scale ETL pipeline development with understanding of data quality, error handling, and automation in high-volume environments.
Skilled in performance engineering for ETL processes and large dataset handling using parallel processing and incremental loading.
Collaborative working style with Salesforce developers and QA teams and capability to document pipeline designs and error patterns effectively.