Experience

Remote

Databricks-native Data and AI consultancy that takes enterprise AI from pilot to production through senior-led, fixed-scope engagements.

Charlotte, NC

Databricks’ four-year Partner of the Year, backed by Databricks Ventures. I was the client-facing technical lead on two to three concurrent lakehouse builds and migrations, and I set the Databricks delivery standard the engagement teams worked inside.

• Led two to three concurrent client engagements as the client-facing technical lead, owning architecture decisions, delivery quality, and risk on each. Four in total across Entertainment, Finance, Healthcare, and Real Estate. Unity Catalog, Lakeflow Declarative Pipelines, and Databricks Asset Bundles were the standard toolchain, across Azure, AWS, and GCP.
• Entertainment: led a Snowflake-to-Databricks migration of a player-cohort analytics platform onto a medallion architecture, with config-driven loads over Lakehouse Federation, automatic cluster-key detection, watermark incrementals, and a hardened MERGE on Liquid Clustering. Onboarding a new source table became one line of config rather than new code.
• Built the validation framework that became that migration’s sign-off gate: schema, row-count, and SHA-256 regression checks plus tolerance-based statistical comparison against the source, running 114 automated checks per run across 678M migrated rows with no per-table rule code. It caught a live source-side load error the source system itself never surfaced, and an AI/BI dashboard put the evidence in front of non-technical stakeholders.
• Designed the gated agentic workflow built to carry that standard to the wider ~500-pipeline estate. A person approves its architecture decisions row by row before verifier-gated build stages run, then a 22-subagent model-tiered bench reviews the output adversarially and persists one READY, NEEDS-CHANGES, or NOT-READY verdict. A repair pass cannot turn a red verdict green.
• Finance: engineered and presented the Databricks proof of concept migrating a legacy homegrown pipeline onto a modern lakehouse, supporting a ~$1.5MM Microsoft and Databricks ECIF proposal and feeding the firm’s business development pipeline.
• Real Estate: owned the code analysis behind a BigQuery-to-Databricks migration whose scope widened mid-engagement from a workflow proof of concept to replacing a 2,000-task orchestration monolith. Warehouse access was never granted, so I scored complexity from the client’s repository through a Databricks Model Serving endpoint, and produced the level-of-effort model, duration bands, and wave sequencing the plan was funded on: ~6,800 hours for the transformation component.
• Designed and built the proof of concept that carried it: the Databricks-native equivalent of the client’s DAG framework, a prototype pipeline demonstrating dependency ordering and execution, and a developer guide and recording so their engineers could extend it. That five-week assessment converted to an executed SOW with partner funding approved, and the migration moved into delivery.
• Healthcare: led a cross-functional team of data engineers and visualization developers through a hospital billing engagement, refactoring 100+ fact and dimension tables, data marts, and Power BI semantic models off Epic Clarity and Caboodle into one modeled layer. Migrated 26 Epic Clarity cube views at 1:1 parity and built the reconciliation that signed the work off: 7.4M source keys accounted for, 18 of 18 tables passed. Delivered under HIPAA constraints on a VNet-injected workspace, with Unity Catalog row- and column-level security and SCIM-synced group access.
• Set the Databricks delivery standard the engagement teams built inside, covering workload translation, validation, testing, and deployment, and enforced it through review on every engagement.
• Mentored data engineers and visualization developers across engagement teams of 3–6, providing technical guidance and code review, and authoring the practice standards they worked against.
• Built the agentic tooling the practice ran on: Model Context Protocol and Claude Agent SDK systems that automate workload translation, validation, and deployment for platform migrations.

• Databricks
• Unity Catalog
• Lakeflow Declarative Pipelines
• Databricks Asset Bundles
• PySpark
• SQL
• Medallion architecture
• Snowflake
• BigQuery
• dbt
• Fivetran
• Astronomer
• Epic Clarity / Caboodle
• Power BI
• MCP
• Claude Agent SDK
• Azure / AWS / GCP

Six months between roles, spent completing the MIT xPRO Data Engineering certificate.

• Completed the MIT xPRO Professional Certificate in Data Engineering, a multi-course program assessed on graded work. It is listed with its verification link on /credentials.

Title of record: Data Analytics Engineer · Remote

Smart-home and pro-AV manufacturer. I owned the pipelines and the certified metrics behind OvrC product analytics, and held the Scrum Master and Data Product Owner roles alongside the engineering work.

• Established the data governance framework: anomaly detection, CI/CD-enabled quality checks, version control, and gold-metric certification, so leadership trusted the numbers it acted on.
• Developed and automated 15+ Databricks pipelines integrating IoT and SaaS sources, contributing to a 50% EBITA increase (~$50M) and a multi-million-dollar ARR customer win.
• Served as Scrum Master for two geographically dispersed US and EU data science teams, shaping shared development practices across time zones and running internal data summits to build cross-team collaboration.
• Transformed hardware sales strategy as Data Product Owner, driving a 3–5x quarterly increase in customer spending through insights that changed product management decisions.
• Standardized and optimized 100+ SQL queries and BI reports across Power BI and Databricks, improving execution speed 40% and lifting executive adoption 60%.
• Led vendor selection and integration for the Heap.io product analytics program, and negotiated third-party contracts with Heap, Ookla, and New Relic to increase ROI across product and engineering.
• Became the internal technical authority for OvrC product analytics, shaping the data narrative from product managers through to the board.

• Databricks
• SQL
• Python
• Power BI
• ETL / ELT
• Data governance
• CI/CD
• AWS
• Heap.io

Charlotte, NC

Fortune 150 utility. I sat between engineering and the business on an internal digital product portfolio.

• Drove metrics strategy across 39 digital products using product-led growth and A/B testing, enabling leadership to track ROI against $75M in targeted operational savings.
• Delivered the insights that secured ~$400K in recurring funding every 8–12 weeks, accelerating digital product delivery.
• Cut time to market 45% by combining Agile delivery with product-led practices.
• As Product Owner, owned a ~$3M business case to scale product development and implement metered funding across Duke Energy IT.

• SQL
• Python
• Power BI
• A/B testing
• Agile
• Jira

Greater New York City Area

Process mining software. I modeled enterprise processes as digital twins and turned what they revealed into a case executives would fund.

• Modeled enterprise processes as digital twins, surfacing inefficiencies and automation opportunities that supported ~$10M in business cases and secured executive buy-in.
• Validated and presented those cases to executive leadership, propelling automation programs that expanded profit margins.
• Ran discovery workshops with cross-functional stakeholders, using process visualizations to clarify data lineage and reporting requirements.

• Celonis
• Process mining
• SQL
• Python
• Discovery workshops

Charlotte, NC

Syndicated credit facilities. My first data role, and where I learned that a number nobody trusts is worse than no number.

• Represented the bank as Agent Bank, coordinating trades, amendments, and daily borrower activity across $12.5B and €2.3B syndicated credit facilities, 52 institutional borrowers, and 3,100+ investors.
• Built the data quality checks and validation processes behind multimillion-dollar reconciliations between borrowers, agents, and lenders, resolving production issues rather than adjusting figures to agree.
• Delivered daily visual reports to senior leadership evidencing resolution of self-identified audit issues.

• SQL
• Data quality
• Reconciliation
• Financial reporting