Experience

My journey in data engineering spans over 6 years, working with diverse teams and technologies to build scalable data solutions. Here's a timeline of my professional experience and achievements.

Professional Experience

Senior Data Engineer

Kinesso

Aug 2025 - Present

Current

Architect and optimize large-scale Snowflake pipelines integrating multi-channel marketing and analytics data across diverse ecosystems.

Key Achievements

•Lead development of Airflow-orchestrated ingestion and transformation workflows, automating report delivery for global campaigns
•Establish data quality monitoring frameworks using dbt tests and automated row-count checks, reducing manual QA cycles by 70%
•Optimize warehouse performance and cost through adaptive scaling and partition strategies, improving dashboard responsiveness by 65%
•Coordinate with cross-functional analytics, BI, and platform teams to ensure compliance, audit readiness, and service-level reliability
•Mentor junior engineers on dbt modularity, Git branching standards, and Snowflake optimization techniques

Technologies Used

Snowflake

dbt

Airflow

AWS

GCP

Python

SQL

Terraform

Docker

GitHub Actions

Tableau

Data Engineer – AI Infrastructure & Pipelines (Freelance)

Stomble / Independent Projects

Jan 2025 - Aug 2025

Delivered production-ready cross-cloud data pipelines supporting AI-driven semantic search, retrieval-augmented generation (RAG), and analytics dashboards.

Key Achievements

•Built Azure SQL, BigQuery, and Snowflake warehouse layers optimized for reliability and performance
•Designed dbt pipelines with Great Expectations-based testing and schema version control achieving 99.9% data accuracy
•Automated CI/CD deployments using Terraform, Docker, and GitHub Actions, reducing release time by 60%
•Published open-source reference projects showcasing RAG pipelines, streaming ETL, and governance automation

Technologies Used

Python

SQL

Azure

BigQuery

Snowflake

dbt

Terraform

Docker

GitHub Actions

Data Engineer

Aluminium Stewardship Initiative (ASI)

Feb 2023 - Jan 2025

Built an end-to-end data warehouse on GCP integrating multiple source systems into a centralized repository.

Key Achievements

•Cut ETL runtime by 40% through Python and DuckDB optimization and dbt-based transformations
•Developed event-driven pipelines via Kafka and Pub/Sub for real-time data synchronization
•Automated infrastructure provisioning with Terraform and IaC, reducing manual operations by 70%
•Delivered APIs and dashboards for analytics and audit reporting, supporting data governance and cost reduction initiatives

Technologies Used

Python

SQL

GCP

dbt

Kafka

Pub/Sub

Terraform

DuckDB

Data Engineer (Healthcare Analytics)

University of Wollongong / Dementia Training Australia

Jun 2022 - Jan 2023

Automated clinical and financial data ingestion pipelines, reducing manual workload by 80%.

Key Achievements

•Automated clinical and financial data ingestion pipelines, reducing manual workload by 80%
•Integrated Cloud Functions and Airflow for hybrid scheduling and monitoring
•Enhanced data modeling for research-ready datasets and optimized dashboards for BI tools

Technologies Used

Python

SQL

GCP

Airflow

Cloud Functions

dbt

Data Specialist

HERE Technologies

Feb 2019 - Dec 2021

Developed and optimized large-scale ETL pipelines using Hadoop, AWS, and Spark.

Key Achievements

•Developed and optimized large-scale ETL pipelines using Hadoop, AWS, and Spark
•Containerized processing jobs using Docker and Kubernetes, improving deployment efficiency
•Implemented secure data governance frameworks and designed distributed data processing solutions for geospatial analytics

Technologies Used

Python

SQL

Hadoop

AWS

Spark

Docker

Kubernetes

Technical Skills

Programming Languages

Python

SQL

JavaScript

Data Platforms

DuckDB

BigQuery

GCP

Streamlit

Cloud Platforms

Google Cloud

AWS

Azure

Data Tools

dbt

LangChain

FastAPI

Power BI

Pandas

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Professional Experience

Senior Data Engineer

Kinesso

Aug 2025 - Present

Current

Architect and optimize large-scale Snowflake pipelines integrating multi-channel marketing and analytics data across diverse ecosystems.

Key Achievements

•Lead development of Airflow-orchestrated ingestion and transformation workflows, automating report delivery for global campaigns
•Establish data quality monitoring frameworks using dbt tests and automated row-count checks, reducing manual QA cycles by 70%
•Optimize warehouse performance and cost through adaptive scaling and partition strategies, improving dashboard responsiveness by 65%
•Coordinate with cross-functional analytics, BI, and platform teams to ensure compliance, audit readiness, and service-level reliability
•Mentor junior engineers on dbt modularity, Git branching standards, and Snowflake optimization techniques

Technologies Used

Snowflake

dbt

Airflow

AWS

GCP

Python

SQL

Terraform

Docker

GitHub Actions

Tableau

Data Engineer – AI Infrastructure & Pipelines (Freelance)

Stomble / Independent Projects

Jan 2025 - Aug 2025

Delivered production-ready cross-cloud data pipelines supporting AI-driven semantic search, retrieval-augmented generation (RAG), and analytics dashboards.

Key Achievements

•Built Azure SQL, BigQuery, and Snowflake warehouse layers optimized for reliability and performance
•Designed dbt pipelines with Great Expectations-based testing and schema version control achieving 99.9% data accuracy
•Automated CI/CD deployments using Terraform, Docker, and GitHub Actions, reducing release time by 60%
•Published open-source reference projects showcasing RAG pipelines, streaming ETL, and governance automation

Technologies Used

Python

SQL

Azure

BigQuery

Snowflake

dbt

Terraform

Docker

GitHub Actions

Data Engineer

Aluminium Stewardship Initiative (ASI)

Feb 2023 - Jan 2025

Built an end-to-end data warehouse on GCP integrating multiple source systems into a centralized repository.

Key Achievements

•Cut ETL runtime by 40% through Python and DuckDB optimization and dbt-based transformations
•Developed event-driven pipelines via Kafka and Pub/Sub for real-time data synchronization
•Automated infrastructure provisioning with Terraform and IaC, reducing manual operations by 70%
•Delivered APIs and dashboards for analytics and audit reporting, supporting data governance and cost reduction initiatives

Technologies Used

Python

SQL

GCP

dbt

Kafka

Pub/Sub

Terraform

DuckDB

Data Engineer (Healthcare Analytics)

University of Wollongong / Dementia Training Australia

Jun 2022 - Jan 2023

Automated clinical and financial data ingestion pipelines, reducing manual workload by 80%.

Key Achievements

•Automated clinical and financial data ingestion pipelines, reducing manual workload by 80%
•Integrated Cloud Functions and Airflow for hybrid scheduling and monitoring
•Enhanced data modeling for research-ready datasets and optimized dashboards for BI tools

Technologies Used

Python

SQL

GCP

Airflow

Cloud Functions

dbt

Data Specialist

HERE Technologies

Feb 2019 - Dec 2021

Developed and optimized large-scale ETL pipelines using Hadoop, AWS, and Spark.

Key Achievements

•Developed and optimized large-scale ETL pipelines using Hadoop, AWS, and Spark
•Containerized processing jobs using Docker and Kubernetes, improving deployment efficiency
•Implemented secure data governance frameworks and designed distributed data processing solutions for geospatial analytics

Technologies Used

Python

SQL

Hadoop

AWS

Spark

Docker

Kubernetes