From Pipelines to Predictions — I Build Smart, Scalable Cloud AI Systems
Let's ConnectWith over a decade of experience in the financial sector, I began as a Data Engineer mastering Oracle, Talend, and ETL design. As the cloud era emerged, I transitioned into machine learning and cloud technologies — now building smart, scalable systems powered by AWS, GCP, Databricks, and AI.
Specialized in building end-to-end ML pipelines on cloud platforms
Expert in data processing at scale with Spark, Airflow and serverless architectures
Experienced in transitioning legacy systems to modern cloud-native solutions
Proficient in MLOps practices and continuous delivery of ML models
My technical toolkit spans data engineering, cloud platforms, machine learning, and modern DevOps practices.
A selection of my most impactful work showcasing my expertise in data engineering, machine learning, and cloud architecture.
Real-time analytics with Spark, Airflow, and S3. Deployed on Docker with Tableau for insights.
The goal is to create a unified customer view for analytics and business intelligence dashboards.
The pipeline efficiently processes IoT, energy, and AI workflow data using event-driven architectures.
Identifies trends, bottlenecks, and anomalies in real-time transaction logs.
Professional credentials validating my expertise in cloud platforms, data engineering, and machine learning.
Validated expertise in designing distributed systems on AWS.
Can readily clean, visualize and summarize data analysis technic.
Conduct a hypothesis test to identify insights about data.
Advanced data visualization and business intelligence skills.
This interactive guide will help you prepare for common cloud experiences.
This interactive guide will help you prepare for common AWS interview questions when transitioning from a Data Engineering role to a Cloud Engineering position. Review these questions and answers to boost your confidence and technical knowledge.
We'll compare AWS database services and clarify where and how to use each for your cloud-native architectures.
Insights and experiences from my journey in data engineering, cloud computing, and machine learning.
In this personal article, I share the challenges, learning curves, and rewards of transitioning from traditional data engineering to modern cloud-based machine learning architecture.
A personal and professional journey from the structured world of Data Engineering to the dynamic realm of Machine Learning in the cloud.
Talend, a leading data integration platform, provides a robust solution for seamlessly transitioning your on-premises database to Snowflake’s cloud-based data warehouse.
Learn how to implement a real-time monitoring system using Kafka, Elasticsearch, and Kibana to detect anomalies in transaction logs.
Interested in working together or have a question about my experience? I'd love to hear from you.
Dhaka, Bangladesh
Available for remote work worldwide