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Nkosi Felix

Senior Data Platform Engineer

Governed ingestion, streaming data, and AI-safe evidence systems.

Azure · Kafka · Python · SQL · Microsoft Graph · SharePoint · PostgreSQL · GitLab CI/CD

U.S. citizen · No sponsorship required · Orlando, FL / Remote · Immediate availability

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Hiring Manager Proof

Architecture, validation, failure modes, tests, and evidence-backed answers.

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Use-Case Labs

Small governed data workflows that turn messy inputs into reviewable outputs.

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Why this is different

This portfolio is built like an evidence system, not a brochure. Public claims route through a versioned evidence ledger, generated manifest, policy checks, and unsupported-claim rejection.

That is the same engineering pattern shown in the labs: validate inputs, preserve provenance, route exceptions, expose boundaries, and keep automation reviewable.

View hiring manager proof → · What this site demonstrates →

Experience snapshot

Lead Software Engineer (W2 Contract) — Universal Creative / NBCUniversal (most recent publicly listed role)

  • Governed ingestion: Python document-ingestion harness and checkpointed Microsoft Graph/SharePoint delta-sync with parser provenance and review bundles.
  • ACCEPT/QUARANTINE/SYSTEM-failure routing and guarded ClickUp automation, preserving owner approval over every status change.

Software Engineer II (Data Engineer) — 4C Strategies North America

  • Idempotent Kafka-to-PostgreSQL consolidation service with replay handling, DTO/schema validation, and paginated APIs.
  • Grafana/Prometheus/Loki observability and GitLab CI contract-test gates (JUnit 5, Mockito, Spring Cloud Stream test binder).

Earlier roles: Senior Cloud Solutions Architect at Accenture (Microsoft Advanced Azure Engagement) and Senior Data Analyst / Data Engineer at Flexport.

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Recruiter Snapshot

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Hiring Manager Proof

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Use-Case Labs

Small data engineering applications that show how messy signals become governed decisions. Synthetic or public data only.

Synthetic data only

Patient Signal Intake Lab

Synthetic care-event intake: schema validation, quarantine routing, review packets.

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Synthetic data only

Grid Event Quality Monitor

Synthetic grid/meter telemetry: timestamp validation, drift detection, degraded-data handling.

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Synthetic data only

Field Change Order Evidence Tracker

Synthetic field change requests: document intake, duplicate detection, owner-approval boundary.

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Mirrors this site's own chat

Evidence-Grounded RAG Evaluator

How this site's own chat rejects unsupported claims before you ever see them.

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Engineering Principles

The same principles that govern the labs and this site's own chat assistant.

Public Reference Projects

Personal, clean-room reference implementations — synthetic data only, no confidential employer code.

7/7 tests passing

Acceptance Harness

Deterministic, infrastructure-free Java 17 validation harness for XMPP-sourced message ingestion.

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26/26 tests passing

Air-Gap Messaging Ingest & Observability

Idempotent Kafka-to-PostgreSQL ingest pipeline with Grafana/Prometheus/Loki observability.

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Synthetic data only

ShopLabs Lakehouse Lab

Clean-room D2C commerce lakehouse using Python and DuckDB with synthetic, seedable order data. No real customer or payment data.

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Synthetic data only

CareerAssistAI Scoring Pipeline

Clean-room FastAPI service scoring resume/job-description overlap with a transparent rationale. No private tracker data.

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Certifications

How Answers Are Generated

Architecture diagram: User leads to Model Orchestrator, which leads to Policy Engine, which leads to Evidence Engine, which leads to Validated Response. A dashed boundary marks the Model Orchestrator as the only stage that calls an external, untrusted LLM provider. A solid boundary marks the Policy Engine, Evidence Engine, and Validated Response as this repository's own code, running after the external call returns. External LLM call This repository (backend/main.py) User Model Orchestrator Policy Engine Evidence Engine Validated Response

Next steps