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.
Great focus on program risk identification and timely reporting and devising action to address it.
Cost benefit analysis and justification to investments.
Planning and project management:
Project planning, scheduling & 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.
Stakeholder Engagement:
Reports to CXO level executives with program status update, risk management and outcomes.
Collaborate with business units, IT teams, and compliance officers to identify governance priorities and resolve data-related challenges.
Facilitate the Data Governance Council meetings and ensure effective decision-making.
Serve as a point of contact for internal and external auditors regarding data governance-related queries.
Compliance and Risk Management:
Ensure adherence to industry regulations and banking-specific compliance requirements.
Identify and mitigate risks related to data usage, sharing, and security.
Monitoring and Reporting:
Develop key performance indicators (KPIs) and metrics to measure the effectiveness of the Data Governance Program.
Provide regular updates to CXO level executive leadership on program status, risks, and outcomes.
Prepare and present audit and compliance reports as required.
Team Leadership and Mentorship:
Lead cross-functional teams, including data stewards, analysts, and governance professionals.
Provide training and mentoring to promote awareness and understanding of data governance practices.
Technical Expertise:
Understanding 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, Collabra data quality, cloud platforms (AWS, Azure, GCP), and data governance frameworks
Qualifications:
Bachelor’s degree in computer science, Data Management, Business Administration, or a related field; MBA or equivalent experience preferred.
16+ 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.
Key Competencies:
Strong strategic thinking and problem-solving skills.
Ability to work under pressure and manage multiple priorities.
Exceptional leadership and interpersonal skills.
Proficiency in program management tools and methodologies.
Strong analytical and decision-making capabilities.
