Lead Data & Solutions Architect

Lead the architecture and technical design of data platforms, data integration strategies, and analytics solutions for client engagements.

• Design, enhance, and modify enterprise data warehouse environments to support evolving client analytics, reporting, and business intelligence needs.
• Design, build, and optimize ETL/ELT pipelines to support data integration, migration, and analytics initiatives across client environments.
• Serve as the senior technical resource in pre-sales and scoping conversations, partnering with practice leadership, and accounting teams to shape solutions and estimate delivery approaches.
• Design data architectures supporting M&A integration efforts, including data consolidation, migration, and harmonization across disparate source systems.
• Architect data solutions tailored to the needs of investment firms (e.g., portfolio data aggregation, deal data management, reporting/analytics for fund operations)
• Apply AI and generative AI tools to enhance data platform delivery - e.g., AI-assisted data engineering, automated data quality and documentation, and Copilot-style development acceleration - ensuring data foundations are fit for purpose.
• Develop data governance, data quality, and data modeling standards and advise clients on adoption.
• Comfortable working with APIs to manage, build and monitor data flows across integrated systems.
• Design and build data pipelines using integration platforms such as Boomi, Celigo, Workato, or MuleSoft
• Architect near-time, real-time and streaming data solutions using event-driven and pub/sub patterns to support low-latency analytics and reporting.
• Oversee technical delivery teams during implementation, providing architectural guidance and quality assurance.
• Produce client-ready architecture diagrams, technical roadmaps, and executive-level presentations.
• Stay current on emerging data platforms, integration, and AI tooling, and bring point-of-view to clients and internal practice development.
• Mentor junior architects and engineers within the practice.

Solution Areas You’ll Deliver As Lead Data & Solution Architect, you will design and lead delivery across the following practice offerings:

• Data Integration / Migration (+ Analysis): Source-to-target analysis, integration design, and migration execution across complex, multi-system environments
• Data Governance Implementation: Standing up governance frameworks, stewardship models, and policy enforcement for clients.
• Data Warehousing / Data Lakehouse Strategy: Designing warehouse and lakehouse architectures, including but not limited to Medallion structure (bronze/silver/gold layering)
• Master Data Management (MDM): Leading end-to-end MDM offerings - domain modeling, match/merge strategy, stewardship workflows, and platform implementation
• Data Analytics & Reporting / Real-Time Analytics & Dashboards: Designing analytics architectures and real-time, streaming-based dashboard/reporting solutions
• Power Platform: Architecting solutions using PowerApps, Power BI, Power Query, and related Microsoft Power Platform tools
• Platform & Software Evaluation & Selection: Leading client stakeholders through evaluation and selection processes for applications, tools, and platforms - including data platform/tool evaluations and vendor selection
• System Integration: Architecting integration between disparate client systems as part of broader data or platform initiatives
• Data Security & Compliance: Designing data protection, access control, and privacy/compliance safeguards appropriate to regulated client environments

• 10+ years in data architecture, data engineering, or solution architecture roles, with several years in a lead or principal capacity
• Prior experience within a Management & IT Consulting firm is strongly preferred - including client delivery leadership, mentorship and advisory of junior consultants, and contributions to firm thought leadership (e.g., points-of-view, whitepapers, conference speaking, and/or internal capability development); comfort working across multiple concurrent client engagements
• Demonstrated experience supporting M&A-related data integration or carve-out projects
• Industry experience in Oil & Gas or Power/Utilities is preferred (not required). Additional favorable industry backgrounds include Financial Services, Construction, Healthcare, and Private Equity
• History of designing and delivering enterprise-scale data platforms
• Required: proven experience designing, enhancing, and modifying enterprise data warehouse environments
• Required: hands-on, tactical experience designing, building, and troubleshooting ETL/ELT pipelines using modern data integration tools
• Practical experience applying AI and generative AI tools within data platform engineering and delivery (e.g., AI-assisted development, automated data quality/testing, Copilot-style coding assistants)
• Familiarity with Work IQ and/or connecting to MCP (Model Context Protocol) servers to support AI-driven data processing and agentic data workflows
• Familiarity with data security and regulatory compliance considerations (PII handling, encryption, SOC 2, GDPR, CCPA) in client-facing environments
• Hands-on experience delivering client solutions with Power Platform (Power BI, PowerApps, Power Query) and iPaaS/integration platforms such as Boomi, Celigo, Workato, or MuleSoft
• Hands-on experience with data modeling (conceptual, logical, physical) and Master Data Management (MDM) implementations - domain modeling, match/merge strategy, and stewardship workflows
• Familiarity with API design, development, and API gateway management to support data access and system integration
• Bachelor’s degree in computer science, Data/Information Systems, or a related field; Master’s degree a plus. Equivalent hands-on experience will be considered in lieu of a degree
• Strong executive presence - able to communicate technical concepts to non-technical stakeholders and participate credibly in sales conversations
• Direct experience with some, if not all, of the following data and cloud management platforms: Databricks, AWS, Snowflake, Informatica, Azure, Microsoft Fabric, and Palantir
• Required: hands-on development experience with SQL Server (T-SQL), PySpark, and Python - not just familiarity, but proven, tactical coding experience

Skill Sets

• Data architecture and modeling (conceptual, logical, physical), including dimensional modeling (Kimball) and Data Vault methodologies
• Data lineage, metadata management, and business glossary/impact analysis practices
• Familiarity with data mesh and domain-driven data ownership approaches
• Hands-on data integration and ETL/ELT pipeline design and development
• Real-time and streaming data architecture, including event-driven and pub/sub design patterns
• API design, development, and lifecycle management
• API gateway design and management
• Data governance, master data management, and data quality frameworks
• Data security, privacy, and regulatory compliance (PII handling, encryption, SOC 2, GDPR, CCPA)
• Cloud data platform design and cost/performance optimization
• DataOps practices, including version control, CI/CD for data pipelines, and pipeline orchestration
• Practical application of AI and generative AI tools to enhance data engineering, development, and delivery workflows
• Familiarity with agentic AI integration patterns, including MCP (Model Context Protocol) server connectivity, for data processing workflows
• Solution scoping, estimation, and technical proposal writing
• Vendor licensing models and cost negotiation for platform and tool selection
• Strong verbal and written communication; comfortable presenting to C-suite audiences
• Team leadership and mentorship

• Platform & Tool Experience Data Management Platforms: Snowflake, Databricks, Azure/Fabric, AWS, Palantir, Informatica

• Data Integration/ETL: Hands-on development experience with Fivetran, Informatica, Talend, Azure Data Factory, dbt
• Integration Platforms (iPaaS) / API Design: Boomi, Celigo, Workato, and general API design/development (REST, GraphQL)
• Databases: Hands-on, expert-level SQL Server development (T-SQL, required); working knowledge of PostgreSQL, MySQL, and NoSQL platforms (MongoDB, Cosmos DB)
• Data Governance/Catalog: Collibra, Alation, Microsoft Purview
• Cloud Ecosystems: Familiarity with AWS, Azure
• AI-Assisted Data Tools: GitHub Copilot, Databricks Assistant, Microsoft Copilot (Fabric/Power Platform), and other AI-assisted development, documentation, or data-quality tools
• AI/Agentic Integration: Work IQ; connecting to and building against MCP (Model Context Protocol) servers for AI-driven data processing and agentic workflows
• BI/Analytics: Power BI, Tableau
• DataOps/Orchestration: Git-based version control, CI/CD (Azure DevOps, GitHub Actions), Airflow, Databricks Workflows
• Languages: Hands-on development experience required in SQL Server (T-SQL, expert level), PySpark, and Python; working knowledge of Spark SQL, Scala, and Bash/Shell scripting
• Documentation & Diagramming: Visio, Lucidchart, draw.io

Preferred Certifications (Not Required)

• Cloud platform certifications (Azure, AWS, or GCP data/architecture tracks)
• Databricks Certified Data Engineer Professional
• Microsoft Fabric Analytics Engineer Associate
• SnowPro (Snowflake) certification
• AWS - Data Engineer, and/or Cloud Practitioner
• Informatica or Palantir certification