Technology / Domain:
Development and maintenance of data pipelines for Salesforce platforms in a banking organization, including system integrations, data flows to/from Data Lake, and ETL/ELT tools on PaaS
Professional Profile/ Required Experience:
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3–5 years of experience as a Data Engineer in Enterprise organizations
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Strong experience building ETL/ELT processes using PaaS tools such as Talend, Informatica Cloud, Azure Data Factory, or similar
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Familiarity with Salesforce data model and CRM data structures
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Experience working with cloud systems and APIs (REST/SOAP)
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Experience with Data Lake / Data Warehouse environments
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Experience with high-volume data processing and regulated environments (banking – advantage) .
Responsibilities:
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Design, develop, and maintain ETL/ELT processes to transfer data to/from Salesforce and Data Lake
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Build API-based integrations between Salesforce and internal banking systems
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Perform data processing, cleansing, enrichment, and integration from multiple sources
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Troubleshoot data pipelines and optimize existing processes
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Work closely with Salesforce developers, implementers, and data architects
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Produce technical documentation and apply best practices for data quality and security
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Support UAT and provide operational support in an offshore model .
Technical Skills:
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Strong SQL skills
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Experience with tools such as Talend / ADF / Informatica Cloud
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Python for data processing – advantage
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Java – advantage
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Experience with messaging and streaming tools (Kafka / Event Hub) – advantage
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Familiarity with CI/CD processes in data engineering
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Strong understanding of data modeling and data governance
