Data Engineering Lead

On-siteSeniorData EngineerJust posted

✦Role summaryAI-generated

The Data Engineering Lead will drive end‑to‑end delivery of the Marketing Data Platform, overseeing integration, reporting and cloud‑based architecture. They will partner with stakeholders to translate requirements into scalable, secure solutions while leading a delivery team.

Skills required

Cloud computing Data architecture Solution architecture Marketing data platforms Integration Reporting Ai technologies Data modeling ETL Big data Data engineering AI Data governance Data pipelines Azure Databricks SQL Git Data science

About this role

JD: Data Engineering Lead – Data & Marketing Platforms

Experience: 10+ Years

Location: NJ/NY

No of Position: 1

Date of Joining: Immediate

This role is seeking an experienced Technology Manager with strong expertise in Marketing Data Platforms, Data Architecture, Solution Architecture, Cloud & AI Technologies, and Team Leadership. This role’s primary responsibilities are leading delivery teams, gathering business and technical requirements, designing scalable and secure cloud-based solutions, and driving end-to-end architecture decisions.

Core 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 delivery artifacts including 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.

Experience / Skillset Requirements:

10 to 15 (max) years of experience in Data Engineering, Data Modeling & Architecture with good foothold in Azure and Databricks
Worked with Marketing Data and conceptually clear on concepts like Account, Customer, Prospect, Lead, Opportunity, Engagement, Consent etc
Strong in Customer 360 and MDM concepts with multiple System Integrations.
Strong Communication and Positive Attitude. Good Problem Solver.
Lead and manage a team of 5-8 or more Data engineers, architects, and technical specialists.

CategoryResponsibilities

Delivery leadership Planning, Risks, Dependencies, Status, Escalations Business partnership Requirements, Scope, Prioritization, Stakeholder Communication Technical leadership Azure, Databricks, SQL/RDBMS, Git, Integration patterns, Customer 360/MDM, Data Modeling, Copilot, Claude, Github Copilot Data governance Quality, Controls, Lineage, Documentation, Data Privacy & Security Team leadership Mentoring, Agile ceremonies, Design reviews Domain Marketing (B2B), Analytics

Responsibilities

Oversee organizational data engineering solutions. Lead highimpact initiatives. Ensure alignment with organizational goals. Provide executive guidance.