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