Building data systems that scale.
Automated provisioning and deployment.
# Airflow DAG Pipeline from airflow import DAG from airflow.operators import \ PythonOperator with DAG('etl_daily', schedule='@daily', start_date=datetime(2024,1,1)): extract = PythonOperator( task_id='extract')
7
Projects Completed
# Airflow DAG Pipeline
from airflow import DAG
from airflow.operators \
import PythonOperator
from datetime import datetime
with DAG('etl_daily',
schedule='@daily',
start_date=datetime(2024,1,1),
catchup=False):
extract = PythonOperator(
task_id='extract',
python_callable=extract_data)
transform = PythonOperator(
task_id='transform',
python_callable=transform_data)
load = PythonOperator(
task_id='load',
python_callable=load_to_dwh)
validate = PythonOperator(
task_id='validate',
python_callable=run_dq_checks)
# Task dependencies
extract >> transform
transform >> load
load >> validateCore competencies in data engineering, cloud infrastructure, and modern development tools.
A selection of data engineering projects showcasing end-to-end pipeline development, automation, and cloud infrastructure expertise.
End-to-end data synchronization pipeline for employee, member roles, and account management with comprehensive failure logging.
Modern Data Stack implementation with containerized ELT system, automated workflows, and real-time data quality monitoring.
Test automation framework for CMS migration using SeleniumBase, enabling automated QC and content verification.
Backend development and refactoring for EU legal data platform, including web crawlers, authentication, and subscription systems.
Data stack audit and optimization for analytics infrastructure, including BigQuery, Fivetran, and BI tool evaluation.
Career progression focusing on data engineering, cloud infrastructure, and building scalable data systems.
Focusing on Modern Data Stack, architecting end-to-end containerized ELT pipelines using Airflow and DBT.
Designed and implemented data synchronization pipelines and audited cloud data architectures for enterprise clients.
Refactored backend systems and built automation frameworks for testing and content migration.
Specialized in software development with focus on data systems and cloud computing.
Cloud Data Engineering (Target)
AWS/GCP
CI/CD & DevOps for Data Pipelines
Self-learning
Infrastructure as Code & Kubernetes
Self-learning
Lead the design and implementation of end-to-end data infrastructures for complex projects. Master the Modern Data Stack ecosystem to deliver optimized, scalable solutions.
2+ Years
Experience
12+
Projects Delivered
99.9%
Uptime Achieved
I specialize in designing and implementing end-to-end data infrastructures using the Modern Data Stack. My focus is on building ETL/ELT pipelines with tools like Airflow, DBT, and Spark, while ensuring data quality and system reliability.
Currently working as a data engineering, I've delivered solutions for clients across various industries including legal tech, real estate analytics, and enterprise data management.