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Client Technology Lead – Data, Analytics & AI

Job in Paterson, Passaic County, New Jersey, 07501, USA
Listing for: ChabezTech LLC
Full Time position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    Business Systems & Technology Analysis, IT Business Analyst, IT Project Manager
Salary/Wage Range or Industry Benchmark: 150000 - 230000 USD Yearly USD 150000.00 230000.00 YEAR
Job Description & How to Apply Below
Job Description:

Client Technology Lead – Data, Analytics & AI

Location: Edison, New Jersey, USA (or nearby commuting area)

Employment Type: Full-Time

Work Model: Onsite, Client-Facing, Multi-Account

Travel: As required based on client and portfolio needs

Experience: 8+ Years

About the Role

We are seeking an experienced Client Technology Lead – Data, Analytics & AI to drive technical coordination and delivery alignment across multiple client accounts. This role serves as the primary onsite technology contact, bridging client stakeholders, account leadership, and distributed delivery teams.

The ideal candidate will possess a broad understanding of data engineering, analytics, business intelligence, and AI technologies, combined with strong consulting, stakeholder management, solutioning, and delivery coordination skills.

The role requires a hands‑on, client‑focused professional who can translate business requirements into actionable technical solutions, facilitate discovery workshops, develop estimates, support solution design, and build or coordinate proofs of concept (POCs) and proofs of value (POVs).

Key Responsibilities
1. Client Engagement and Delivery Leadership
  • Act as the onsite technical point of contact for multiple client accounts.
  • Coordinate with client stakeholders, account leadership, and distributed or offshore delivery teams.
  • Manage priorities, requirements, dependencies, risks, decisions, and action items to ensure timely execution.
  • Maintain alignment between business objectives, client expectations, and technical delivery.
  • Build trusted relationships with business leaders, technology stakeholders, and product owners.
2. Data, Analytics, BI, and AI Solutioning
  • Participate in technical discussions covering data engineering, analytics, business intelligence, semantic models, and AI.
  • Demonstrate working knowledge of data platforms, pipelines, ETL/ELT, APIs, data warehouses, lake houses, dashboards, and reporting ecosystems.
  • Understand modern AI capabilities, including Generative AI, retrieval‑augmented generation (RAG), and agentic AI.
  • Evaluate solution options, identify technical gaps, and facilitate discussions on architecture, feasibility, and implementation trade‑offs.
  • Engage subject‑matter experts when specialized technical expertise is required.
3. Discovery and Consulting
  • Plan and facilitate discovery workshops with business and technology stakeholders.
  • Gather and structure business requirements, pain points, priorities, constraints, and opportunities.
  • Assess existing data environments, business processes, reporting ecosystems, and technology landscapes.
  • Prepare assessment findings, recommendations, roadmaps, and actionable work packages.
  • Translate complex technical concepts into clear recommendations for business and technical audiences.
4. Solution Design and Estimation
  • Convert business requirements into practical solution approaches, deliverables, assumptions, and dependencies.
  • Prepare and validate effort estimates, resource requirements, staffing plans, and implementation timelines.
  • Collaborate with delivery teams and technology specialists on solution feasibility and delivery planning.
  • Support proposals, solution presentations, client discussions, and project mobilization.
  • Build or coordinate lightweight POCs, POVs, demonstrations, and technical validation exercises.
5. Hands‑on Technical Validation
  • Review SQL queries, datasets, dashboards, semantic models, notebooks, prototypes, and other technical artifacts.
  • Validate proposed data flows, reporting solutions, and proof‑of‑concept implementations.
  • Contribute hands‑on when required to test ideas, validate assumptions, and demonstrate solution capabilities.
  • Identify delivery risks and recommend practical approaches to address technical or…
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