Marketing Data Platform Lead - Azure & Databricks Expert

EXL Talent Acquisition Team; New Jersey; On-site; USD 150,000 - 190,000; Full time

Job summary

EXL Talent Acquisition Team seeks a Data Engineering Lead for its NJ/NY operations to guide marketing data platforms, data architecture, and cloud-enabled solutions. You will lead the delivery team, drive requirements, and shape end-to-end architecture decisions with focus on governance, security, and scalable data pipelines.

The role demands 10+ years in data engineering, strong Azure/Databricks experience, and proven leadership of engineers and architects across data modeling, integration, and

Qualifications

• 10 to 15 years in Data Engineering, Modeling & Architecture with Azure and Databricks.
• Strong in Marketing Data concepts: Account, Customer, Lead, Opportunity, Engagement, Consent.
• Leadership of 5–8+ data engineers and architects; strong communication and problem solving.

Responsibilities

• Lead end-to-end delivery of Marketing Data platform, integration, reporting, and architecture initiatives.
• Partner with stakeholders to clarify requirements, define scope, and translate into delivery plans.
• Manage risks, timelines, decisions, and tradeoffs across teams; maintain RAID and release plans.
• Drive sprint planning, backlogs, technical reviews, and issue resolution.
• Ensure scalable, secure, well-documented solutions aligned with data governance.
• Provide technical leadership across cloud data platforms, data modeling, and activations.

Skills

Data Engineering

Data Modeling

Data Architecture

Azure

Databricks

SQL/RDBMS

Git

Integration patterns

Customer 360/MDM

Cloud & AI

Tools

Copilot

Claude

Github Copilot

Job description

EXL Talent Acquisition Team seeks a Data Engineering Lead for its NJ/NY operations to guide marketing data platforms, data architecture, and cloud-enabled solutions. You will lead the delivery team, drive requirements, and shape end-to-end architecture decisions with focus on governance, security, and scalable data pipelines.

The role demands 10+ years in data engineering, strong Azure/Databricks experience, and proven leadership of engineers and architects across data modeling, integration, and