Data Engineer.Injaz - TECH - Digital Data Platforms.41.MIT

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Data & Analytics Driven Organization: One Data Analytics & AI Function drives the vision to transform the Bank into a Data Driven Organization (DDO) using latest tools and technologies in the Data space.

To lead and manage multiple data and analytics squads - Advanced Analytics (AA), Environmental, Social & Governance (ESG), Corporate Credit & Limit Management (CCLM) Data, and Marketing Campaign Data & Analytics - ensuring delivery of scalable, compliant, and business aligned solutions. The role is accountable for defining the strategic roadmap, driving AI enabled innovation, embedding strong governance and data quality frameworks, and enabling data driven decision making across corporate banking.

Key Responsibilities

• Cluster Leadership & Strategic Direction: Lead multiple squads across Advanced Analytics, ESG Data, and Corporate Credit & Limit Management Data, ensuring seamless delivery of high impact, enterprise scale programs.
• Define and execute the cluster's strategic roadmap, aligning with corporate banking goals, enterprise data strategy, and regulatory priorities.
• Digital Transformation Programs: Oversee the execution of strategic programs for corporate digital banking across regions covering solutions for Trade Finance, Liquidity Management, Payment Systems, and Collections.
• Analytics and Business Intelligence: Deliver end to end BI solutions and business operational reports that support decision making at the executive level.
• Data Engineering and Technology Leadership: Oversee data architecture, big data engineering, and AI driven models to unlock new insights.
• Cross Functional Collaboration: Coordinate with core banking, risk, compliance, and digital transformation teams to create and maintain a unified, agile, and scalable data model.
• Project and Stakeholder Management: Manage timelines, resources, and deliverables while ensuring efficient execution of business critical data projects.
• Compliance and Risk Management: Ensure full compliance with ESG reporting requirements, credit exposure governance, and marketing data privacy regulations.

Qualifications & Experience

• 14+ years of experience in data engineering, analytics, and enterprise data platforms across on premise (Hadoop, Cloudera) and cloud (Azure, Databricks) environments.
• Functional expertise in corporate banking data domains including trade, payments, liquidity, revenues, risk.
• Strong understanding of data governance, compliance, and quality frameworks.
• Knowledge of AI/ML applications in data engineering, predictive analytics, and automation.
• Proficiency in real time processing (Kafka, Spark Streaming) and graph databases (Neo4j).
• Leadership & Strategy - Vision setting, roadmap definition, and squad leadership.
• Program Governance - Managing multi domain, cross functional initiatives.
• AI & Automation - Embedding AI/ML into business processes for efficiency and insights.
• Governance & Compliance - Establishing and enforcing architecture and quality standards.
• Stakeholder Engagement - Influencing and collaborating with executives, regulators, and business leaders.
• Technical Expertise - Guiding teams on high performance, scalable data solutions.
• Significant leadership experience in delivering multi domain data and analytics programs in financial services.
• Proven success in regulatory critical program delivery (ESG, credit risk, marketing governance).
• Track record of managing diverse, cross functional teams to deliver strategic business outcomes.

Seniority Level

Director

Employment Type

Full time

Job Function

Information Technology

Industries

Banking

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