Data Architect / Technical Lead

KData AI; United States; Remote; CAD 120,000 - 160,000; Full time

Job summary

KData AI is seeking an experienced Data Architect to serve as Technical Lead on a data modernization engagement for a large national not-for-profit. You will guide the current-state assessment, design the target-state architecture, and deliver a practical, phased roadmap to implementation.

You will provide technical direction to an embedded data engineer, work with business analysts to define the first data product, and help the client adopt governance, security, and cataloging capabilities for

Qualifications

• 8+ years in data engineering, data platforms, or analytics.
• 4+ years in a data architecture or technical lead role.
• Experience assessing enterprise data platforms and designing roadmaps.
• Strong knowledge of lakehouse, data warehouse, medallion, data mesh or data product approaches.
• Hands-on experience with Microsoft Azure and Databricks across the Azure Databricks stack.

Responsibilities

• Review the existing Enterprise Data Platform architecture and assess governance, security, metadata, and operations.
• Plan and lead stakeholder interviews and workshops with technology, architecture, data and analytics teams.
• Define the future-state architecture and formulate a phased implementation roadmap.
• Partner with business analysts to identify candidate business use cases and translate them into technical requirements.
• Provide technical oversight to the embedded data engineer and ensure alignment with the target-state architecture.
• Present findings and recommendations to technical teams and senior leadership.

Skills

Data architecture

Technical leadership

Stakeholder workshops

Azure Databricks stack

Data governance

Tools

Azure Data Lake Storage

Azure Data Factory

Delta Lake

Unity Catalog

Databricks workflows

Microsoft Purview

Collibra

Alation

Job description

We are seeking an experienced Data Architect to serve as Technical Lead on a data modernization engagement with a large national not-for-profit organization. The client is planning the next evolution of its Enterprise Data Platform into a governed, scalable enterprise data foundation that will support reporting, analytics, data governance, and future AI initiatives.

You will lead a structured assessment of the client’s current platform, design the target-state architecture, and produce a practical, phased roadmap to implementation. You will also provide technical direction to an embedded data engineer and work alongside business analysts to define the client’s first business-focused data product, which will become the foundation for a Proof of Concept in 2027. This is a hands‑on advisory role that calls for strong architectural judgement and the ability to earn the trust of both technical and business stakeholders quickly.

Key Responsibilities

This is a remote position.

Data Architect / Technical Lead

Current-State Assessment & Discovery

• Review the existing Enterprise Data Platform architecture, including data ingestion, storage, transformation, and consumption layers.
• Assess platform capabilities and maturity across governance, security, metadata management, and operational processes.
• Plan and lead stakeholder interviews and workshops with Technology, Architecture, Data & Analytics, Governance, and business teams.
• Identify strengths, limitations, and technical debt, and validate how existing investments align with the client’s future-state vision.
• Reconcile platform documentation against the actual implementation, where the two differ.
• Produce the Current-State Architecture Assessment.

Target‑State Architecture & Blueprint

• Define the future‑state enterprise data platform architecture.
• Define governance and operating‑model requirements, including roles, ownership, and decision rights.
• Specify security, data lineage, metadata, and data cataloging capabilities.
• Establish architectural principles and implementation priorities.
• Identify required platform capabilities, dependencies, and gaps.
• Develop a phased, realistic implementation roadmap.
• Produce the Target‑State Architecture and Gap Analysis & Roadmap deliverables.

Data Product Discovery & Definition

• Partner with business analysts to facilitate workshops that identify and prioritize candidate business use cases.
• Translate business objectives, success measures, source systems, data requirements, and consumption needs into technical considerations.
• Define implementation implications and implementation‑ready requirements for a future Proof of Concept.
• Author the High‑Level Solution Design and contribute to the Initial Data Product Definition Document.

Technical Leadership

• Provide technical oversight and design guidance to the embedded data engineer supporting pipeline development and backlog delivery.
• Ensure engineering work in flight is consistent with the emerging target‑state architecture.
• Support knowledge transfer to client personnel so the client can own and extend the architecture.
• Surface risks early, such as stakeholder availability, access delays, and shifting requirements, and work with the client project lead to resolve them.
• Present findings and recommendations clearly to technical teams and senior leadership.

Qualifications

Required

• 8+ years of experience in data engineering, data platforms, or analytics, including at least 4 years in a data architecture or technical lead role.
• Demonstrated experience assessing existing enterprise data platforms and designing target‑state architectures and roadmaps.
• Strong knowledge of modern data platform patterns such as lakehouse, data warehouse, medallion architecture, and data mesh or data product approaches.
• Strong, hands‑on experience with both Microsoft Azure and Databricks, including designing and delivering enterprise data platforms on the Azure Databricks stack (for example Azure Data Lake Storage, Azure Data Factory, Delta Lake, Unity Catalog, and Databricks workflows).
• Solid understanding of data governance, metadata management, data lineage, data cataloging, and data security and privacy controls.
• Experience defining data operating models, including ownership, stewardship, and roles.
• Proven ability to facilitate workshops and interviews with both business and technical stakeholders.
• Excellent written communication, with a track record of producing clear architecture documents, gap analyses, and solution designs.
• Comfort working to tight timelines in a client‑facing consulting environment.

Preferred

• Consulting or professional services experience delivering assessment and blueprint engagements.
• Experience in the not‑for‑profit, humanitarian, healthcare, or public sector.
• Familiarity with governance and cataloging tools (for example Microsoft Purview, Unity Catalog, Collibra, or Alation).
• Experience preparing data platforms for AI and machine learning use cases.
• Relevant certifications (for example Azure Solutions Architect Expert, Azure Data Engineer Associate, Databricks Certified Data Engineer Professional, TOGAF, or CDMP).