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Architect (Level: Manager)
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CREQ227430 Requisition #
We are seeking a Data Engineer with strong expertise in SQL and ETL processes to support banking data quality data pipelines, regulatory reporting, and data quality initiatives. The role involves building and optimizing data structures, implementing validation rules, and collaborating with governance and compliance teams. Experience in the banking domain and tools like Informatica and Azure Data Factory is essential. Strong proficiency in SQL for writing complex queries, joins, data transformations, and aggregations
Proven experience in building tables, views, and data structures within enterprise Data Warehouses and Data Lakes
Strong understanding of data warehousing concepts, such as Slowly Changing Dimensions (SCDs), data normalization, and star/snowflake schemas
Practical experience in Azure Data Factory (ADF) for orchestrating data pipelines and managing ingestion workflows Exposure to data cataloging, metadata management, and lineage tracking using Informatica EDC or Axon
Experience implementing Data Quality rules for banking use cases such as completeness, consistency, uniqueness, and validity
Familiarity with banking systems and data domains such as Flexcube, HRMS, CRM, Risk, Compliance, and IBG reporting
Understanding of regulatory and audit readiness needs for Central Bank and internal governance forums Write optimized SQL scripts to extract, transform, and load (ETL) data from multiple banking source systems
Design and implement staging and reporting layer structures, aligned to business requirements and regulatory frameworks
Apply data validation logic based on predefined business rules and data governance requirements
Collaborate with Data Governance, Risk, and Compliance teams to embed lineage, ownership, and metadata into datasets
Monitor scheduled jobs and resolve ETL failures to ensure SLA adherence for reporting and operational dashboards
Support production deployment, UAT sign off, and issue resolution for data products across business units 3 to 6 years in banking-focused data engineering roles with hands on SQL, ETL, and DQ rule implementation
Bachelors or Master's Degree in Computer Science, Information Systems, Data Engineering, or related fields
Banking domain experience is mandatory, especially in areas related to regulatory reporting, compliance, and enterprise data governance

We are seeking a Data Engineer with strong expertise in SQL and ETL processes to support banking data quality data pipelines, regulatory reporting, and data quality initiatives. The role involves building and optimizing data structures, implementing validation rules, and collaborating with governance and compliance teams. Experience in the banking domain and tools like Informatica and Azure Data Factory is essential. Strong proficiency in SQL for writing complex queries, joins, data transformations, and aggregations
Proven experience in building tables, views, and data structures within enterprise Data Warehouses and Data Lakes
Strong understanding of data warehousing concepts, such as Slowly Changing Dimensions (SCDs), data normalization, and star/snowflake schemas
Practical experience in Azure Data Factory (ADF) for orchestrating data pipelines and managing ingestion workflows Exposure to data cataloging, metadata management, and lineage tracking using Informatica EDC or Axon
Experience implementing Data Quality rules for banking use cases such as completeness, consistency, uniqueness, and validity
Familiarity with banking systems and data domains such as Flexcube, HRMS, CRM, Risk, Compliance, and IBG reporting
Understanding of regulatory and audit readiness needs for Central Bank and internal governance forums Write optimized SQL scripts to extract, transform, and load (ETL) data from multiple banking source systems
Design and implement staging and reporting layer structures, aligned to business requirements and regulatory frameworks
Apply data validation logic based on predefined business rules and data governance requirements
Collaborate with Data Governance, Risk, and Compliance teams to embed lineage, ownership, and metadata into datasets
Monitor scheduled jobs and resolve ETL failures to ensure SLA adherence for reporting and operational dashboards
Support production deployment, UAT sign off, and issue resolution for data products across business units 3 to 6 years in banking-focused data engineering roles with hands on SQL, ETL, and DQ rule implementation
Bachelors or Master's Degree in Computer Science, Information Systems, Data Engineering, or related fields
Banking domain experience is mandatory, especially in areas related to regulatory reporting, compliance, and enterprise data governance

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