Senior Data & AI Engineer · Phoenix, AZ · Available for Freelance

Data infrastructure
that drives decisions.

I help fintech companies and growth-stage startups build reliable data systems and AI-powered automation — so their data actually works for them.

Work With Me See My Work
Fortune 500
Caliber experience
5+
Years of production experience
10× Faster
Data systems that actually perform
100+
Solutions governed end-to-end
About

Enterprise-grade experience.
Startup-ready agility.

I'm Ramiz Khatib — a senior data engineer with hands-on experience building production-scale data systems at Fortune 500 companies. I know what it takes to build infrastructure that doesn't break when it matters most.

I work with fintech startups and growth-stage companies that need serious data engineering without the overhead of a full-time hire. That means fast pipelines, clean data models, and AI automation that actually ships.

Based in Phoenix, AZ. Working remotely with teams across the US.

// Experience
Wells Fargo
Senior Analytics Consultant · Data & AI Engineer · 2023–Present
Deloitte
Data Analyst Intern · 2022
Florida International University
B.S. Business Analytics & Information Systems
Services

What I build for you.

End-to-end data engineering across pipelines, analytics, and AI — for any company that runs on data.

01
Data Pipeline Engineering
Scalable ELT/ETL systems that process millions of rows reliably. From raw ingestion to clean, queryable data — built to run without you babysitting them.
02
Analytics & Reporting
Turn raw data into decisions. I design data models and build dashboards your team will actually use — with the governance and data quality to trust what they show.
03
AI & Agent Development
From automating data workflows with LLMs to building fully autonomous agents that monitor pipelines, surface anomalies, and take action — I design the data infrastructure that makes AI actually work in production.
Projects

Work that ships.

Real projects with real results — built end to end.

↗
Batch · Financial Data
Plaid Financial Pipeline
Cloud-native ELT pipeline ingesting 500K+ transactions via Plaid REST API — orchestrated with Airflow, transformed in PySpark, modeled in dbt with schema tests, loaded into BigQuery.
500K+
Transactions
Star Schema
Data model
AirflowdbtPySparkBigQuery
↗
Real-Time · Stream Processing
Flight Risk Data Pipeline
Real-time pipeline using Spark Structured Streaming and Kafka to ingest live flights into BigQuery, enriched with conflict zone risk scores via Claude AI. Deployed on GCP with Docker and CI/CD.
10K+
Live flights
Real-time
Grafana dashboard
PySparkKafkaBigQueryClaude AIGCP
↗
Batch · Multi-Cloud
NYC Rideshare Pipeline
Automated batch ELT pipeline ingesting 100K+ NYC TLC trip records using Mage AI, dual-loaded into BigQuery and Snowflake for multi-cloud analytical workloads with geospatial KPIs.
100K+
Trip records
Multi-cloud
BQ + Snowflake
Mage AIBigQuerySnowflakeLooker
↗
Enterprise · Governance
Audit Change Management System
Architected a full change management pipeline at a major financial institution using the JIRA API, governing 100+ solutions across Dev → UAT → Prod with data quality validation at each stage.
100+
Solutions governed
3-stage
Deployment pipeline
JIRA APISQL ServerSSISAlteryx
Stack

Tools I work with.

// Languages
Python (Pandas, PySpark)
SQL
Bash / Shell
TypeScript
// Data Pipelines
Apache Airflow
Apache Kafka · Flink
dbt · Prefect
SSIS · Alteryx · Mage AI
Databricks
// Cloud & Infra
BigQuery · Redshift · Synapse
GCS · S3 · Blob Storage
Docker · Kubernetes · Terraform
CI/CD · Git
Snowflake · SQL Server
// Agentic AI (Claude)
Claude Agent SDK
MCP (Model Context Protocol)
Claude Managed Agents
Anthropic API (Opus · Sonnet · Haiku)
Multi-Agent Orchestration
// AI & LLM
RAG Pipeline Design
LangChain · LangGraph
LlamaIndex · CrewAI
Pinecone · Weaviate · pgvector
LangSmith (Observability)
// BI & Reporting
Tableau · Power BI
Looker Studio · Grafana
Dremio
Blog

Latest thinking.

Practical insights on data engineering, AI, and the modern data stack.

↗
Featured · May 2026
Why Your Data Pipeline is Slower Than It Should Be
Most slow pipelines aren't a compute problem — they're a design problem. Here's what I've learned building pipelines that cut execution from hours to minutes.
Data & AIPerformancedbt
↗
Mar 2026 · 5 min read
AI Agents for Data Teams: What's Actually Useful in 2026
Everyone's talking about AI agents. But which ones are actually production-ready? I break down what's working, what's hype, and what I'm building with.
AI AgentsLLMs
View All Articles →
Contact

Let's build something.

Have a data problem worth solving? I take on a limited number of projects at a time — reach out and let's talk about yours.

rnk.analytics@gmail.com
LinkedIn GitHub Email