Lead Data & Solutions Architect

Role Overview

MRE Consulting’s Data Strategy & Cloud Enablement practice — part of our Project Delivery Services division — is seeking a Lead Data & Solution Architect to serve as a senior technical authority across client engagements, spanning multi-system integrations, data management platform implementations, and key data initiatives.

This is a client-facing, firsthand architecture role: you will design data platforms and solutions, translate ambiguous business problems into technical roadmaps, and function as the trusted technical voice in sales and delivery conversations alongside our consulting leads.

This role suits someone who is equally comfortable in a team whiteboarding session, strategy session with a client’s CTO, CIO, or CDO, and in the granularity of a data model or pipeline design — and who enjoys the variety of a boutique consulting environment where every engagement looks different.

Key Responsibilities

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.

[[JD_HEADING:Solution Areas You’ll Deliver

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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

Preferred Experience

• 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