VP/Director of Data & Intelligence Engineering Resume Leo Pitts VP/Director of Data & Intelligence Engineering (919) 555-0148 leo.pitts@protonmail.com linkedin.com/example/leopitts Raleigh, NC 27609 STRENGTHS Technical Direction Set shared architecture standards across client programs; engineers gained clearer decisions and delivery teams had fewer repeated debates. People Development Career plans, pairing, and candid feedback helped senior contributors step into broader ownership; mentoring became a trusted part of team culture. Client Translation Turned executive business questions into practical data architectures; clients found a partner who could speak plainly about tradeoffs. Responsible AI Raised governance, sovereignty, and access concerns early; security and compliance partners gained confidence in delivery decisions. Retrieval Quality Introduced Golden Sets and RAGAS reviews for uncertain answers; teams gained a shared language for improving context quality. SKILLS Data architecture Zero-ETL Lakehouse Data contracts Data governance Data lineage Python PySpark Expert SQL Azure AWS GCP Vector databases Knowledge graphs MCP connectors LANGUAGES English Native 40 Spanish Intermediate 20 MY CAREER 14.9 Years Vice President, Data & Intelligence Engineering at Blue Ridge Intelligence Partners (5.5 Years) Director, Applied Data Platforms at Meridian Cloud Advisory (3.6 Years) Senior Data Engineering Manager at Crescent Harbor Financial (3.4 Years) Data Engineering Lead at Summit Retail Systems (1.3 Years) Data Engineer at Harborview Analytics Lab (1.1 Years) SUMMARY Data and Intelligence Engineering executive with 14 years building modern data platforms and leading multidisciplinary teams across consulting, financial services, and regulated enterprise environments. Brings nine years of people leadership for teams of five to fourteen engineers and senior individual contributors. Translates client problems into governed lakehouse, semantic, retrieval, graph, and agentic architectures that support dependable business outcomes. Production delivery spans Zero-ETL, real-time streaming , Python, PySpark, SQL, Databricks, Snowflake, Synapse, Fabric, Azure, vector stores, knowledge graphs , MCP connectors, Graph-RAG, RAGAS, Golden Set testing , and policy-as-code . Partners with architecture, design, security, governance, and executive groups to improve delivery quality, coach technical talent, and advance responsible AI practices. EXPERIENCE Vice President, Data & Intelligence Engineering Blue Ridge Intelligence Partners March 2021 - Present Raleigh, NC Leads a 14-person consulting engineering organization delivering governed Data Foundation platforms, retrieval services, semantic systems, and agentic solutions for regulated clients. Owns technical standards, coaching, architecture decisions, governance participation, and delivery quality across multidisciplinary programs. Set Layer 1 standards with Zero-ETL and data contracts for repeatable client delivery outcomes Launched Pinecone , Weaviate, and Neo4j foundations for retrieval and graph intelligence programs Deployed MCP connectors for Jira, CRM, ERP, and lakehouse sources with secure access controls Defined Data, Reasoning, and Validation hand-offs with AI architecture and design leaders Established RAGAS, Golden Set, and retrieval observability practices for production probabilistic systems Coached engineers through architecture reviews and career plans, preparing emerging technical leaders Represented engineering in AI Ethics forums covering governance, sovereignty, and responsible AI guardrails Director, Applied Data Platforms Meridian Cloud Advisory July 2017 - February 2021 Durham, NC Managed a nine-person consulting delivery group responsible for cloud data platforms, lakehouse programs, semantic roadmaps, and early enterprise retrieval solutions. Converted executive priorities into governed architectures, coached senior contributors, and strengthened production readiness across 11 client programs. Directed 11 client programs across Azure, Databricks , Snowflake , Synapse, and Fabric platforms Translated executive objectives into lakehouse roadmaps with ownership, lineage, and service expectations Built Python and PySpark frameworks combining batch, streaming, and Zero-ETL ingestion patterns Guided LangChain , GPT, and Claude retrieval programs with baselines and escalation paths Partnered with solutions architecture and interface design leaders on integrated platform delivery Introduced Golden Sets and evaluation workflows for low-confidence response handling Prepared senior contributors for broader ownership through reviews, mentoring, and architecture workshops Senior Data Engineering Manager Crescent Harbor Financial January 2014 - June 2017 Richmond, VA Supervised seven engineers delivering governed analytical datasets and streaming services for risk, compliance, and relationship-management stakeholders. Directed warehouse modernization, security controls, semantic modeling, operational reliability, executive communication , and structured development for engineering talent. Modernized warehouse processing with Python , PySpark , and expert SQL for regulated reporting Implemented Snowflake and Azure controls for identity, classification, lineage, and sensitive data access Unified CRM and ERP concepts through semantic modeling, reducing reporting reconciliation effort Introduced dimensional modeling and non-relational access patterns for risk data products Established monitoring, SLA reviews, incident response , and root-cause analysis across pipelines Presented architecture risks to executives, compliance partners, and business sponsors Developed engineers through structured feedback, technical pairing, and delivery retrospectives Data Engineering Lead Summit Retail Systems August 2012 - December 2013 Columbus, OH Led a six-person engineering pod building a cloud analytics foundation for merchandising, inventory, and customer engagement teams. Shaped reusable pipelines, secure data services, graph modeling, migration practices, mentoring, and release consistency across business domains. Built Python and SQL components validating schema drift, late data, and duplicate records Migrated workloads to Azure and Databricks with documented contracts and lineage Created Neo4j product and supplier models supporting relationship discovery for analysts Exposed curated data services through secure APIs and consistent integration patterns Mentored junior engineers through reviews, design walkthroughs, and release retrospectives Improved testing and deployment consistency through reusable delivery documentation Data Engineer Harborview Analytics Lab June 2011 - July 2012 Columbus, OH Built foundational data workflows for customer and operations reporting while developing practical depth in Python, SQL, PySpark, Azure, testing, and production support. Strengthened data quality practices through reconciliation, source mapping, and structured investigation of failed loads. Built Python and SQL workflows for customer and operations reporting datasets Created PySpark transformations for historical files with recurring reconciliation checks Modeled relational reporting tables and documented source-to-target business definitions Supported Azure storage and notebook analysis through a supervised platform proof of concept Added unit tests and deployment notes that clarified analyst hand-offs Investigated failed loads through query analysis and structured root-cause documentation PROJECTS Enterprise Agent Data Fabric 2025 Aligned engineers, architects, and client stakeholders around semantic layers, vector retrieval, graph context, and secure MCP access. Shared design decisions openly, giving teams a practical foundation for agent workflows and production review. Probabilistic Retrieval Quality Program 2023 Brought delivery, governance, and client teams together around chunking, RAG optimization, RAGAS, evals, and Golden Set testing. Created a calmer review process for uncertain answers and clearer decisions about production readiness. Regulated Lakehouse Modernization 2020 Worked with finance and operations partners to connect business definitions with lakehouse architecture, lineage, contracts, and service expectations. The group moved forward with shared ownership rather than isolated platform decisions. LEADERSHIP & AWARDS Responsible AI Practice Recognition, Blue Ridge Intelligence Partners, 2024 Client Innovation Award, Meridian Cloud Advisory, 2020 Engineering Mentor of the Year, Crescent Harbor Financial, 2016 EDUCATION Master of Science in Computer Science North Carolina State University GPA: 4.0 2011 Raleigh, NC Coursework: Data Engineering, Artificial Intelligence, Database Systems, Distributed Computing Bachelor of Science in Information Technology University of Cincinnati GPA: 4.0 2009 Cincinnati, OH Coursework: Database Management, Systems Analysis, Software Engineering, Information Security CERTIFICATIONS Microsoft Certified: Azure Data Engineer Associate 2023 Databricks Certified Data Engineer Professional 2022 SnowPro Advanced: Data Engineer 2021 Microsoft Certified: Azure Solutions Architect Expert 2020 TECHNICAL SKILLS Programming: Python, PySpark, SQL Data Platforms: Databricks, Snowflake, Synapse Cloud Services: Azure, AWS, GCP Microsoft Data: Fabric, Entra ID, Synapse Vector Stores: Pinecone, Weaviate, Milvus Graph Systems: Neo4j, Graph-RAG, knowledge graphs Agent Frameworks: LangChain, LangGraph, CrewAI Foundation Models: GPT, Claude, Gemini Retrieval Evaluation: RAGAS, evals, Golden Set testing Data Architecture: Lakehouse, Zero-ETL, streaming Security Controls: OAuth, row-level security, column-level security Governance: Data contracts, lineage, policy-as-code Integration Sources: Jira, CRM, ERP Operations: Observability, SLA design, incident response Responsible AI: AI Ethics, model governance, data sovereignty SKILLS Data architecture Zero-ETL Lakehouse Data contracts Data governance Data lineage Python PySpark Expert SQL Azure AWS GCP Vector databases Knowledge graphs MCP connectors PROFESSIONAL AFFILIATIONS AI Ethics and Governance Working Group, Blue Ridge Intelligence Partners, 2022 - Present Triangle Data Engineering Meetup, Volunteer Technical Speaker, 2019 - Present Data Architecture Center of Excellence, Chair, Meridian Cloud Advisory, 2018 - 2021 LANGUAGES English (Native) Spanish (Intermediate) ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. ADDITIONAL INFORMATION Work Status : Authorized to work in United States. No sponsorship required. REFERENCES AVAILABLE ON REQUEST
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