Job Summary:

We are seeking a results-driven Data Project Manager (PM) to lead data initiatives leveraging Databricks and Confluent Kafka in a regulated banking environment. The ideal candidate will have a strong background in data platforms, project governance, and financial services, and will be responsible for ensuring successful end-to-end delivery of complex data transformation initiatives aligned with business and regulatory requirements.

Key Responsibilities:

Project Planning & Execution

• Lead planning, execution, and delivery of enterprise data projects using Databricks and Confluent.
• Develop detailed project plans, delivery roadmaps, and work breakdown structures.
• Ensure resource allocation, budgeting, and adherence to timelines and quality standards.

Stakeholder & Team Management

• Collaborate with data engineers, architects, business analysts, and platform teams to align on project goals.
• Act as the primary liaison between business units, technology teams, and vendors.
• Facilitate regular updates, steering committee meetings, and issue/risk escalations.

Technical Oversight

• Oversee solution delivery on Databricks (for data processing, ML pipelines, analytics).
• Manage real-time data streaming pipelines via Confluent Kafka.
• Ensure alignment with data governance, security, and regulatory frameworks (e.g., GDPR, CBUAE, BCBS 239).

Risk & Compliance

• Ensure all regulatory reporting data flows are compliant with local and international financial standards.
• Manage controls and audit requirements in collaboration with Compliance and Risk teams.

Required Skills & Experience:

✅ Must-Have:

• 7+ years of experience in Project Management within the banking or financial services sector.
• Proven experience leading data platform projects (especially Databricks and Confluent Kafka).
• Strong understanding of data architecture, data pipelines, and streaming technologies.
• Experience managing cross-functional teams (onshore/offshore).
• Strong command of Agile/Scrum and Waterfall methodologies.

✅ Technical Exposure:

• Databricks (Delta Lake, MLflow, Spark)
• Confluent Kafka (Kafka Connect, kSQL, Schema Registry)
• Azure or AWS Cloud Platforms (preferably Azure)
• Integration tools (Informatica, Data Factory), CI/CD pipelines
• Oracle ERP Implementation experience

✅ Preferred:

• PMP / Prince2 / Scrum Master certification
• Familiarity with regulatory frameworks: BCBS 239, GDPR, CBUAE regulations
• Strong understanding of data governance principles (e.g., DAMA-DMBOK)

Education:

Bachelor’s or Master’s in Computer Science, Information Systems, Engineering, or related field.

KPIs:

• On-time, on-budget delivery of data initiatives
• Uptime and SLAs of data pipelines
• User satisfaction and stakeholder feedback
• Compliance with regulatory milestones