Director – AI/ML Engineering

Jobtailor; Chennai District; On-site; INR 4,000,000 - 8,000,000; Full time

Job summary

Verizon is seeking a senior data engineering leader to guide a team of data engineers, architects and managers focused on corporate and financial analysis domains. You will architect data solutions across cloud and on-prem environments, drive AI-first data strategies, and foster an inclusive, high-performing culture in Chennai.

You will mentor senior staff, define strategic objectives, enable platform modernization, and oversee governance, cost optimization, and delivery of impact across large,

Qualifications

• Bachelor’s degree with eight or more years of relevant Data engineering and leadership experience.
• Fifteen or more years of overall work experience.
• Experience leading and building Data and AI-infused engineering teams.
• Experience with GCP, modern data platforms, Big Data and Hadoop.
• Experience in Data Architecture and applying AI to the data lifecycle.
• Strong Corporate Services and financial-domain knowledge, with Telecom expertise preferred.
• Willingness to travel up to approximately 15% of the time.
• Master’s degree in Computer Science or MBA preferred as an additional qualification.
• Experience driving significant cost optimization on Google Cloud.

Responsibilities

• Lead a team scaling and managing Data Engineering solutions for Verizon Corporate and Financial Analysis domains.
• Lead people managers, senior data engineers and architects.
• Devise AI strategies to streamline data intake through consumption.
• Build data solutions and services on premise, in the cloud and/or on the edge for real-time and batch workloads.
• Promote Data Medallion Architecture and Federated Data Engineering practices.
• Establish data reliability and governance disciplines covering lineage, quality, classification and secure access controls.

Skills

Data Engineering Leadership

AI Strategy Implementation

GCP & Big Data Expertise

Data Architecture Experience

Cost Optimization on Google Cloud

Education

Bachelor's degree

Master’s Degree in Computer Science or MBA

Tools

Google Cloud Platform

Big Data

Hadoop

Data Medallion Architecture

Data Services

Cloud Migration

Job description

• Lead a team scaling and managing Data Engineering solutions for Verizon Corporate and Financial Analysis domains
• Lead people managers, senior data engineers and architects
• Build data solutions and services on premise, in the cloud and/or on the edge for real-time and batch workloads
• Devise AI strategies to streamline data intake through consumption
• Build a diverse team, leadership pipeline and inclusive culture
• Attract and retain engineering talent and drive employee satisfaction
• Mentor and guide senior data experts and people leaders
• Enable career development through training, coaching and mentoring
• Define and continuously measure objectives and key results
• Develop strategies for business needs aligned with organizational vision through stakeholder dialogue
• Implement modern data industrialization practices across cloud, Big Data and database ecosystems
• Drive platform modernization and cloud migration activities
• Promote Data Medallion Architecture and Federated Data Engineering practices
• Apply an AI-first approach by building data context layers for intelligent insights
• Implement reusable data optimization techniques and enterprise data services using an automate-first methodology
• Establish data reliability and governance disciplines covering lineage, quality, classification and secure access controls
• Ensure adherence to SLAs and FinOps cost-optimization practices
• Serve as a technical thought leader and advisor
• Maintain an external industry presence and advance the Verizon brand
• Track AI and data technology advances and apply them to enterprise problems
• Foster innovation through patents, open source and publications
• Inspire creation of monetizable services for Verizon and its partners

Requirements

• Bachelor’s degree with eight or more years of relevant Data engineering and leadership experience
• Fifteen or more years of overall work experience
• Experience leading and building Data and AI-infused engineering teams
• Specific experience with GCP, modern data platforms, Big Data and Hadoop
• Experience in Data Architecture
• Experience applying AI to the data lifecycle
• Experience delivering business outcomes in large and complex organizations
• Experience communicating complex designs and outcomes to non-technical audiences
• Willingness to travel up to approximately 15% of the time
• Master’s degree in Computer Science or an MBA preferred as an additional qualification
• Strong Corporate Services and financial-domain knowledge, with Telecom expertise preferred
• Experience implementing AI, Gen AI and Agentic AI solutions into engineering practice preferred
• Experience in end-to-end Product lifecycle management preferred
• Experience driving significant cost optimization on Google Cloud preferred

Core Competencies

Demonstrates expertise in leading Data Engineering teams and implementing AI strategies to optimize data solutions across cloud and on-premise environments. Proven ability to drive business outcomes through innovative data practices and effective stakeholder communication.

Highest-signal resume keywords

• Data Engineering Leadership
• AI Strategy Implementation
• GCP and Big Data Expertise
• Data Architecture Experience
• Cost Optimization on Google Cloud

ATS Optimization Keywords

Hard Skills

• Data Engineering
• AI Implementation
• Data Architecture
• Big Data
• Hadoop
• Cloud Migration
• Data Medallion Architecture
• Data Optimization Techniques
• Data Governance
• FinOps Practices

Soft Skills

• Mentoring
• Team Building
• Stakeholder Communication
• Employee Satisfaction
• Innovation Fostering

Certifications & Qualifications

• Bachelor’s Degree
• Master’s Degree in Computer Science or MBA

Industry Keywords

• Corporate Services
• Financial Domain Knowledge
• Telecom Expertise
• Data Lifecycle
• Product Lifecycle Management

Tools & Technologies

• Google Cloud Platform
• Modern Data Platforms
• Data Services
• Real-Time Data Solutions
• Batch Workloads