Cloud Data Engineering Solution Leader

Capgemini • New York, NY

2d • $155,000 - $210,000 • Hybrid

About The Position

We are seeking a Cloud Data Engineering Solution Leader to innovate, define, and build an autonomous Agentic Data Platform spanning data engineering and data management across multiple hyperscalers and cloud ecosystems.
The platform will accelerate data modernization and enable our Financial Services covering Banking and Insurance clients to be 'AI‑ready' and 'agentic‑ready' through reusable architecture, accelerators, and enterprise‑grade operationalization.

Requirements

• 15+ years of experience in data platforms, data engineering, and/or data management; with 5+ years leading solution architecture, platform engineering, or productized accelerators.
• Multi‑cloud experience across at least two hyperscalers (Azure/AWS/GCP) and modern data platforms (e.g., Databricks, Snowflake).
• Strong expertise in modern data engineering patterns (batch/streaming, CDC, orchestration), lakehouse architectures, and scalable data operations.
• Deep knowledge of data management disciplines: governance, metadata, data quality, lineage, MDM/reference data, privacy/security controls.
• Experience embedding AI/GenAI/Agentic AI into data operations to deliver measurable efficiency and reliability improvements.
• Proven ability to influence senior stakeholders (CIO/CDO/CTO) and translate complex technology into business outcomes.
• Strong leadership in global, matrixed organizations-able to build communities, mentor teams, and drive execution through ambiguity.
• Experience with agent orchestration frameworks and patterns (tool use, planning, memory), retrieval/grounding (RAG), and enterprise evaluation/observability for agentic systems.
• Experience building industry accelerators for regulated environments (Banking, Capital Markets, Insurance) including governance and audit requirements.
• Background in managed services / platform operations (SRE, reliability engineering) and cost optimization across data platforms.

Responsibilities

• Own the end‑to‑end vision, strategy, and roadmap for an autonomous Agentic Data Platform (data engineering + data management) across Azure, AWS, Google Cloud, Databricks, Snowflake, and hybrid environments.
• Lead solution architecture and engineering to deliver a configurable, metadata‑driven platform with reusable accelerators and reference implementations.
• Institutionalize a single core codebase (with governed branching) and modern DevSecOps practices for secure, repeatable releases.
• Establish and govern always‑on demo/reference environments for GTM, partner showcases, and client PoCs; define funding and cost‑governance (FinOps) to sustain environments.
• Build autonomous capabilities for ingestion, transformation, quality, lineage, policy enforcement, AI governance/guardrails, and single‑pane observability, including 'self‑healing' patterns.
• Drive evolution of data products and semantic layers to enable trusted, business‑ready consumption and AI use cases at scale.
• Partner with Sales, GTM, and Alliances to shape differentiated propositions (Fixed Bid / Managed Services / outcome‑based), support strategic pursuits/RFPs, and jointly build partner momentum.
• Own adoption: enable delivery teams, define operating model & documentation, and ensure no dependency on any one individual.
• Provide technical governance across active engagements where the solution is implemented or committed, ensuring delivery success and continuous improvement.

Benefits

• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits like subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees