I build data systems that don't fall apart under real pressure.

AI-Augmented Senior Data Engineering Consultant specializing in scalable architectures, resilient pipelines, and GenAI-driven workflows. Trusted by global teams to untangle complexity and future-proof platforms.

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7+
Years Experience
4+
Industry Domains
5+
Speaking Events
∞
Curiosity
Get to Know Me

About Me

Hamza Nasir

Hi, I'm Hamza Nasir — The Big Data Lad

I'm an AI-Augmented Senior Data Engineering Consultant with 7+ years of experience building scalable, resilient data platforms. I help teams design, optimize, and modernize data systems that actually hold up in production and future-proof them with GenAI-Driven workflows.

I specialize in:

✓ Databricks & Apache Spark
✓ Apache Kafka & Streaming
✓ AWS Cloud Architecture
✓ GenAI & LLM Workflows
✓ Large-Scale Batch & Streaming Pipelines
✓ RAG Architectures
✓ Custom CDC Implementations
✓ Agent-Based Automation
✓ Performance Optimization
✓ Cost Reduction Strategies

Based remotely & globally available, I work with distributed teams across time zones, focused on outcomes over tools. Let's build something that holds up under real pressure.

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Why Work With Me

Track Record

⚡
7+ years building real-world data systems across healthcare, finance, telecom, and research domains
🎤
Speaker at AWS Cloud Club, AI Nexus, Cloud Nexus, and university workshops
✍️
Writing about data engineering and architecture at bigdatalad.com
🎯
Focused on production-grade systems, not slideware — real solutions for real problems
🌐
Experienced in async-first remote work with globally distributed teams across multiple time zones
🔄
End-to-end ownership mindset, from architecture design through deployment and production monitoring
Services

What I Actually Help Teams With

I solve complex data engineering challenges that are slowing you down or keeping you up at night.

🏗️

Scalable Data Pipelines

Designing scalable data platforms that survive growth and don't crumble under pressure.

🔧

Pipeline Repair

Fixing fragile pipelines and architectural bottlenecks that cause production fires.

🔄

CDC & Ingestion

Building resilient CDC and ingestion systems when off-the-shelf tools fall short.

🤖

GenAI Workflows

Implementing GenAI workflows that improve real productivity, not just demos.

🚀

Production Hardening

Turning "it works locally" systems into production-grade, battle-tested platforms.

🧭

Technical Leadership

Providing architectural guidance and hands-on leadership for distributed teams.

Selected Work

Projects That Shipped

Real systems built for real teams — not hypotheticals or proof-of-concepts.

Healthcare / Research

Large-Scale Databricks Platform & Gene Expression Pipeline

High-scale biological and medical datasets requiring strong architectural foundations, governance, and reliability from day one.

Databricks Delta Lake Unity Catalog Spark
Challenge
Ensuring platform wouldn't become fragile as complexity and scale increased — proactive architecture, not reactive fixes.
Approach
  • End-to-end data lake architecture on Databricks
  • Chunked processing for fault tolerance
  • Governance via Unity Catalog

Highly resilient platform with strong recoverability and long-term stability under increasing scale.

AI / Automation

Multi-Agent AI System for Databricks Deployment

Complex deployment workflows were slowing down engineering teams with manual effort, cognitive load, and inconsistencies.

LLM Agents Databricks API Python NLP
Challenge
Manual deployment processes creating bottlenecks, inconsistencies, and developer frustration.
Approach
  • Agent-based AI with natural language workflows
  • Designed to augment, not replace engineers
  • Focused on practical utility over hype

Faster iteration cycles and measurably improved developer productivity.

Real-Time Data

Real-Time Customer Intelligence Platform using Kafka

Built for a digital banking environment where customer support agents needed access to accurate, real-time customer data while handling live calls.

Kafka Streams Kubernetes Debezium MongoDB
Challenge
Designing full end-to-end real-time platform capable of reliably syncing operational data with low latency and high trust.
Approach
  • Complete architecture with Kafka Streams on K8s
  • CDC using Debezium SQL Server connector
  • ETL pipelines via Kafka Connect + MongoDB sink

Robust real-time ODS enabling confident work with live, trustworthy customer data in production.

Data Platform / Leadership

Large-Scale Financial Data Pipeline (AWS Ecosystem)

Led a team building an end-to-end data platform for processing high-volume financial transactions across multiple pipelines and destinations.

AWS Lambda Step Functions S3 Glue PostgreSQL Snowflake
Challenge
High-volume transactional data required reliable processing, complex CDC handling, and support for multiple downstream consumers without sacrificing consistency or performance.
Approach
  • Led team designing end-to-end AWS-based data pipelines
  • Built transactional processing using Lambda, Step Functions, Glue, and PostgreSQL
  • Designed parallel pipeline to prepare curated datasets for Snowflake ingestion
  • Implemented complex CDC mechanisms for non-trivial data flows

Reliable, production-grade pipelines capable of handling financial-scale data with consistency, traceability, and long-term maintainability.

Data Engineering / Open Source

Configuration-Driven JSON Schema Transformation Engine for Enterprise Data Pipelines

Built a powerful Scala-based JSON transformation engine that maps source JSON structures to target JSON using declarative mapper configurations. Designed for ETL pipelines, data integration, and format conversions.

Scala SBT Lift-JSON JSONPath ETL Design Data Transformation
Challenge
Transforming complex nested JSON structures between different schemas with support for dynamic expressions, CSV lookups, and runtime variable injection—without hardcoding transformation logic.
Approach
  • Designed a declarative mapper configuration supporting 6 transformation types
  • Implemented JSONPath-based field extraction for flexible source navigation
  • Built dynamic Scala expression evaluation for runtime transformations
  • Added CSV lookup integration for external reference data enrichment
  • Created comprehensive logging and error handling for production reliability

A reusable, configuration-driven transformation engine that eliminates custom code for JSON mapping, reduces development time, and ensures consistent, maintainable data pipelines.

Architecture / Documentation

Enterprise Data Mapping & Ingestion Design (Healthcare Domain)

Designed and documented complex end-to-end data mappings for large-scale ingestion and processing workflows in a regulated healthcare environment.

Informatica Data Modeling ETL Design Enterprise Documentation Healthcare Data
Challenge
Complex source systems, strict data correctness requirements, and the need for precise documentation to support large-scale enterprise ingestion workflows.
Approach
  • Designed detailed end-to-end data mapping documents for complex pipelines
  • Collaborated closely with technical and non-technical stakeholders
  • Ensured mappings supported scalability, correctness, and long-term maintainability
  • Structured documentation to serve as a foundation for reliable implementation

Clear, implementation-ready documentation that reduced ambiguity, improved delivery quality, and supported reliable enterprise-scale ingestion.

Sharing Knowledge

Talks & Writing

Speaking at conferences, running workshops, and writing about what I learn.

Panel Speaker

AWS Cloud Club

2025
Panel Speaker

AI Nexus

Industry Conference
Panel Speaker

Cloud Nexus

Industry Conference
Featured Talk

The Future of Data Engineering in the Age of AI Agents

Dice Analytics, Islamabad
Workshop

Data Lakes Deep Dive

COMSATS University, Islamabad

I write about data engineering, architecture patterns, and building production systems.

Read at bigdatalad.com →
How I Work

My Philosophy

I care about building systems that are honest, resilient, and grounded in reality.

I prefer solving complex engineering problems over shipping superficial features. I work best with teams that value clarity, ownership, and long-term thinking.

I actively avoid projects that compromise integrity and focus instead on work that genuinely creates value. I'm comfortable collaborating across time zones with globally distributed teams.

What I Value

🎯
Clarity over complexity
🔒
Production-grade reliability
🤝
Honest communication
🌍
Global collaboration
📈
Long-term thinking
🚀 Available for New Projects

Have a Data Challenge?
Let's Solve It Together.

Whether it's scaling pipelines, architecting data platforms, or integrating AI into your workflows — I'm here to help you build systems that actually work in production.

✉️ Start a Conversation hamza@bigdatalad.com →
✓ Usually respond within 24 hours
✓ No commitment, just a conversation