Data Engineering Lead

EXL • New Jersey, NJ

4d

About The Position

The Data Engineering Lead will lead delivery teams and end-to-end architecture and delivery initiatives for marketing data platforms, integrations, reporting, and architecture. The role partners with business stakeholders to gather and clarify business and technical requirements, define scope and priorities, and translate objectives into delivery plans. It manages risks, dependencies, decisions, timelines, and tradeoffs across business, development, architecture, infrastructure, and operations teams.

The position establishes delivery artifacts, drives sprint planning and other Agile ceremonies, and provides technical leadership across cloud data platforms, data modeling, pipelines, integrations, and downstream reporting or activation use cases. It is responsible for ensuring solutions are scalable, secure, supportable, documented, and aligned with enterprise data governance standards. The role also oversees organizational data engineering solutions, leads high-impact initiatives, supports alignment with organizational goals, provides executive guidance, and leads and mentors a team of data engineers, architects, and technical specialists.

Requirements

• The posting lists 10 to 15 years (maximum) of experience in data engineering, data modeling, and architecture, with a strong foothold in Azure and Databricks.
• Experience with marketing data and conceptual understanding of Account, Customer, Prospect, Lead, Opportunity, Engagement, and Consent.
• Strong understanding of Customer 360 and MDM concepts, including multiple system integrations.
• Ability to lead and manage a team of 5–8 or more data engineers, architects, and technical specialists.
• Strong communication skills, a positive attitude, and problem-solving ability.
• Graduate in Computer Science, Data Science, or a related field.

Responsibilities

• Lead end-to-end delivery of marketing data platform, integration, reporting, and architecture initiatives from intake through production deployment.
• Partner with business stakeholders to clarify requirements, define scope, validate priorities, and translate objectives into executable delivery plans.
• Manage project risks, dependencies, decisions, timelines, and tradeoffs across business, development, architecture, infrastructure, and operations teams.
• Establish and maintain project plans, RAID logs, decision logs, requirements documentation, release plans, and production handoff materials.
• Drive sprint planning, backlog refinement, delivery ceremonies, technical reviews, and issue-resolution discussions.
• Ensure solutions are scalable, secure, supportable, well-documented, and aligned with enterprise data governance standards.
• Provide technical leadership across cloud data platforms, data modeling, data pipelines, integrations, and downstream reporting or activation use cases.
• Lead and manage a team of data engineers, architects, and technical specialists; provide mentoring and executive guidance.
• Oversee organizational data engineering solutions and lead high-impact initiatives aligned with organizational goals.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager