Data & MI automation Project Manager (PM)

نظرة عامة على الوظيفة

  • تاريخ الإعلان
    أبريل 13, 2026
  • الموقع
  • تاريخ إنتهاء الصلاحية
    يونيو 18, 2026

المسمى الوظيفي

411_3455726

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 escalations.

Required 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)

التعليم

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

#J-18808-Ljbffr

2026-04-05 11:46:30