VP-Data Engineering and Governance

Indosat; Indonesia; On-site; USD 150.000 - 200.000; Full time

Job summary

A leading telecommunications company is seeking a Vice President of Data Engineering and Governance to shape its data infrastructure and governance processes. The ideal candidate will drive data strategy, implement scalable architectures, and ensure compliance and quality across data initiatives. This role requires strong leadership and expertise in data engineering and AI technologies.

Qualifications

• Expertise in data engineering, data management, and governance.
• Strong leadership skills in a telecommunications environment.

Responsibilities

• Develop and execute data strategy leveraging AI and machine learning.
• Oversee data engineering systems and ensure compliance with governance policies.
• Manage vendor relationships for data warehousing technologies.

Skills

Data Engineering

Data Governance

AI Technologies

Data Management

Tools

GCP

AWS

Job description

VP-Data Engineering and Governance

Location:

ID:

Level:

Employment Status: Permanent

Department: Group Digital Engineering and Transformation

Description:

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 Responsibilities

1. 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 end-to-end tools and resources to run DWH on public cloud platforms such as GCP, AWS, or others.
• Devise proper FinOps strategies and execute them.
• Ensure architectural governance of cloud implementations.

AI and Business Value Generation

• Champion the use of AI and advanced analytics across the organization, ensuring data is accessible, actionable, and of high value.
• Provide initiatives that generate business value within the DWH domain and implement out-of-the-box cloud AI/ML models and other toolkits.