VP-Data Engineering and Governance

Role Purpose

The Vice President (VP) of Data Engineering and Governance will play a critical role in shaping the future of our data infrastructure, engineering capabilities, and governance processes. This executive position requires a strong leader with expertise in data engineering, data management, data governance, and AI technologies within a highly complex and dynamic telecommunications environment. The VP will drive data strategy, implement scalable data architectures, ensure data quality, compliance, and governance, and lead data engineering teams to deliver world-class solutions.

Job Description

UDP Strategy

• Develop and execute the data strategy to support the company's business goals, with an emphasis on leveraging AI and machine learning capabilities
• Develop and implement a comprehensive strategy for our hybrid data warehouse, including on-premises and cloud-based solutions, to meet the evolving needs of our telecom business.

Data Modelling

• Design and maintain canonical data models that support efficient data storage, retrieval, and analytics while complying with industry standards and best practices.

ETL and ELT Process Optimization and Performance Tuning

• Streamline and optimize the ETL, ELT (Extract, Transform, Load) processes to ensure data is ingested, processed, and transformed efficiently for timely insights.
• Continuously monitor and enhance the performance of the data warehouse system, ensuring that queries and reports are executed quickly and without bottlenecks.

Integration and Engineering

• Oversee the development and optimization of robust, scalable, and secure data engineering systems that drive data pipelines, real-time data processing, and data infrastructure across the company.
• Collaborate with different business units to integrate data from various sources, including network data, customer data, and billing information.

Security, Compliance & Governance

• Ensure that data governance policies, practices, and procedures are effectively implemented across the organization, ensuring data quality, consistency, privacy, and security.
• Implement and enforce data security and compliance measures, ensuring data privacy and regulatory requirements are met in DWH Architecture Model.
• Lead the creation and execution of data stewardship practices to enhance data accuracy and integrity.

Vendor Management

• Work with data warehousing technology vendors to evaluate and select the right tools, platforms, and services to meet our business needs.

Cloud Resource Planning and Management (GCP, AWS and others)

• Plan e2e tools and resources to run DWH on public cloud as in GCP, AWS or any other cloud platform.
• Device proper Finops strategy and execution.
• Ensure the architectural governance of Cloud implementation.

AI and Business Value Generation

• Championing the use of AI and advanced analytics across the organization, ensuring data is accessible, actionable, and of high value.
• Provide Business Value generating initiatives using in the DWH domain and implement OOTB cloud AI/ML models and other toolkits.