Key Responsibilities:
Project Planning & Execution
- Lead planning execution and delivery of enterprise data and MI automation projects using Databricks and Confluent.
- Develop detailed requirements project plans delivery roadmaps and work breakdown structures.
- Ensure resource allocation budgeting and adherence to timelines and quality standards.
- Manage vendors deliverables and quality of output
- Manage issues conflicts and prepare mitigation
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 Skills & Experience:
Must-Have:
- 7 years of experience in Project Management within the banking or financial services sector.
- Proven experience leading data and MI automation 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
- PowerBI
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:
Bachelors or Masters 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
Required Experience:
IC
Key Responsibilities:Project Planning & Execution- Lead planning execution and delivery of enterprise data and MI automation projects using Databricks and Confluent.- Develop detailed requirements project plans delivery roadmaps and work breakdown structures.- Ensure resource allocation budgetin...
Key Responsibilities:
Project Planning & Execution
- Lead planning execution and delivery of enterprise data and MI automation projects using Databricks and Confluent.
- Develop detailed requirements project plans delivery roadmaps and work breakdown structures.
- Ensure resource allocation budgeting and adherence to timelines and quality standards.
- Manage vendors deliverables and quality of output
- Manage issues conflicts and prepare mitigation
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 Skills & Experience:
Must-Have:
- 7 years of experience in Project Management within the banking or financial services sector.
- Proven experience leading data and MI automation 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
- PowerBI
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:
Bachelors or Masters 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
Required Experience:
IC
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