Software Engineering Managing Consultant, Data Architect Professional Burlingame, US

IBM; Burlingame (CA); À distance; USD 180 000 - 230 000; Plein temps

Résumé du poste

IBM Consulting is seeking a Managing Consultant, Data Architect to lead enterprise data & AI platform architecture across diverse engagements. You will shape target-state architectures, drive roadmaps, and ensure governance, security, and data quality are embedded in delivery.

You’ll mentor teams, influence platform choices like Snowflake and Databricks, and contribute to pre-sales with technical narratives.

Qualifications

• Lead enterprise data & AI platform architecture across multiple engagements.
• Define target state and workstreams with trade-offs documented.
• Incorporate security, governance, and data quality considerations from design to delivery.

Responsabilités

• Own end-to-end target-state architecture for data & AI platforms.
• Lead architecture assessments and AI readiness evaluations with executives.
• Design layered data models and select integration patterns.
• Maintain reference architectures and engineering standards.
• Run architecture reviews and guide engagement architects and engineers.
• Set platform adoption direction for Snowflake, Databricks, and related tools.
• Responsible for delivery health and surfacing architectural debt early.
• Lead solutioning, pre-sales, and technical narratives for proposals.

Connaissances

Target-State Architecture

Roadmaps & Advisory

Data Modeling

Security & Governance

Platform Direction

Outils

Snowflake Cortex

Snowpark

Iceberg

Databricks Unity Catalog

Mosaic AI

Description du poste

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You'll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you'll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You'll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences.

Hakkoda, an IBM company, is a modern data and AI consultancy. Our mission is to push the boundaries of data and AI, to be the partner clients trust for their most complex data challenges, and to create the kind of company that people want to be a part of. We bring deep expertise to Snowflake and the broader modern data stack, we are easy to work with, and we turn repeat problems into reusable solutions. Our team is distributed across North America, Latin America, and Europe, and we hire curious people who want to learn, experiment, and lead.

In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers), where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology.

Your role and responsibilities

We are looking for a Managing Consultant, Data Architectto join our growing team of experts. This position is the principal technical authority for enterprise data and AI platforms across a portfolio of client engagements, with Snowflake and Databricks and cloud-native services on AWS, Azure, and GCP alongside it. The work spans target-state architecture and roadmaps, data modeling and integration patterns, security and governance architecture, and the reference architectures and standards that keep delivery consistent across engagements.

The ideal candidate leads architecture through delivery rather than handing off a design. They define the target state, decompose it into workstreams, make and document the trade-offs, and review what engagement teams build against it. They have been the lead architect on multiple enterprise platform implementations, lead discovery and executive advisory with client leadership, and bring a business-first lens to every design decision. They incorporate AI tooling into how they design and deliver, advise clients on AI readiness and where AI fits in their data strategy, and architect platforms that support AI workloads while keeping foundational data quality, structure, and governance intact.

This role carries principal-level ownership and a very high bar for delivery. The Managing Consultant, Data Architectis accountable for the technical outcome across every engagement they govern: the architecture is sound, the standards are followed, what ships to the client meets the design, and client executive sponsors trust them to make and defend the hard technical calls. They set technical direction for engagement architects and lead engineers, run architecture reviews, author the practice's reference architectures, lead solutioning and pre-sales for new work, and grow the practice's architecture bench through mentorship. They lead through technical authority rather than line management and thrive in a consulting environment where no two engagements are the same.

This role can be performed from anywhere in the US.

Responsibilities

• Target-State Architecture:Own end-to-end target-state architecture for enterprise data and AI platforms across concurrent engagements, including platform topology, environment strategy, security and governance model, and cost and performance architecture at advanced-certification depth.
• Roadmaps and Executive Advisory:Lead architecture assessments and AI readiness and data maturity evaluations; translate findings into phased roadmaps with success metrics, investment cases, and cost guardrails; present and defend them to client executives.
• Data Modeling and Integration Patterns:Design layered data models (medallion, dimensional, Data Vault, 3NF) and semantic layers; select and justify integration patterns (batch, CDC, event-driven, API, data sharing) and record the trade-offs as architecture decision records.
• Reference Architectures and Standards:Author and maintain the practice's reference architectures, decision records, and reusable patterns for ingestion, transformation, orchestration, observability, governance, and AI-ready data; define engineering standards for transformation frameworks, CI/CD, and infrastructure as code.
• Architecture Governance:Run architecture reviews for engagement architects and lead engineers; approve or redirect designs before build; resolve cross-engagement design questions.
• Platform Direction:Set adoption direction for platform-native and AI capabilities (for example Snowflake Cortex, Snowpark, Iceberg and open table formats, Databricks Unity Catalog and Mosaic AI) and define where each platform fits in a client's estate, including coexistence and migration architectures.
• Delivery Accountability:Hold the technical outcome through delivery: decompose the architecture into workstreams, review what ships against the approved design, surface architectural risk, scope drift, and technical debt early with proposed resolutions, and partner with project and practice leadership on delivery health.
• Solutioning and Pre-Sales:Own architecture, effort estimates, staffing shapes, and technical narrative for proposals and statements of work; lead technical discovery and solution design in pursuit cycles alongside sales and practice leadership.
• Technical Leadership and Mentorship:Set technical direction for engagement teams; mentor architects, data engineers, and analytics engineers; support hiring, onboarding, and technical enablement for the practice.
• Practice and Partner Contribution:Con