Roles and Responsibilities
Planning, execution, and successful delivery of data engineering projects
- Project initiation and planning: Define project scope, objectives, timelines, budget, resources, and risks.
- Resource management: Allocate, manage, and track the performance of the data engineering team.
- Communication and collaboration: Facilitate communication between stakeholders, including data engineers, data scientists, business analysts, and executives.
- Risk management: Identify, assess, and mitigate project risks proactively.
- Issue resolution: Address project challenges and issues promptly and effectively.
- Monitoring and reporting: Track project progress, measure performance against targets, and report findings to stakeholders regularly.
Key Responsibilities
Program Leadership:
- Develop and execute a comprehensive Data Governance strategy aligned with the organization's objectives and regulatory requirements.
- Act as a liaison between senior leadership, stakeholders, and cross-functional teams to ensure program alignment and success.
- Drive organizational change to establish a culture of data governance and stewardship.
- Focus on program risk identification, timely reporting, and devising actions to address issues.
- Conduct cost-benefit analysis and justify investments.
Planning and project management:
- Project planning, scheduling, and tracking
- Work prioritization and resource planning
- Risk identification and reporting
- Team planning and management
- Status reporting
Governance Framework Implementation:
- Establish and manage a robust Data Governance framework, including policies, standards, roles, and responsibilities.
- Implement data cataloging, metadata management, and data lineage tools to enhance data visibility and accessibility.
- Oversee the creation of workflows and processes to ensure adherence to governance policies.
Technical Expertise:
- Understanding of data engineering principles and practices: Good understanding of data pipelines, data storage solutions, data quality concepts, and data security is crucial.
- Familiarity with data engineering tools and technologies: This may include knowledge of ETL/ELT tools, Informatica IDMC, MDM, data warehousing solutions, Collibra data quality, cloud platforms (AWS, Azure, GCP), and data governance frameworks.
Desired Candidate Profile
- 15+ years of experience in program management, with at least 6+ years focused on data governance or data management with MDM in the banking or financial services sector.
- Strong knowledge of data governance frameworks, principles, and tools (e.g., Collibra, Informatica, Alation).
- Experience with regulatory compliance requirements for the banking industry, such as GDPR, CCPA, BCBS 239, and AML/KYC regulations.
- Proven track record of successfully managing large, complex programs with cross-functional teams.
- Excellent communication and stakeholder management skills, with the ability to influence and align diverse groups.
- Familiarity with data analytics, data quality management, and enterprise architecture concepts.
- Certification in program or project management (e.g., PMP, PRINCE2) or data governance (e.g., DGSP, CDMP) is a plus.