-> Design, build, and maintain efficient and scalable data pipelines to collect, process, and store large volumes of structured and unstructured data from various sources such as social media platforms, web analytics, and customer databases.-> Develop and implement data models, schemas, and data warehousing solutions to enable effective data integration, transformation, and analysis.-> Monitor and optimize the performance of data infrastructure and systems to ensure high availability, reliability, and scalability.-> Provide technical guidance and mentorship to junior members of the team, and help foster a data-driven culture across the organization.

Casual conversations about software engineering - in casual Bangla.

→ Designed system architecture and high-level components for multiple microservice-based backend systems.→ Successfully developed an end-to-end AI-driven product that predicts potential diseases arising from irregular heartbeat using ECG data.→ Contributed to building an object detection framework that can be easily customized for object detection work without requiring machine learning expertise.→ Led the development of Infolytx Cognitive Agent Framework, HAL™ - a proprietary conversational AI framework that seamlessly integrates with existing conversational frameworks such as IBM Watson, Google Dialog Flow, and Amazon Lex to create intelligent task-directed conversational assistants.→ Designed an event-driven chatbot analytics and management platform.→ Spearheaded the containerisation and migration of our existing serverless infrastructure to Kubernetes.→ Actively participated in the execution of the Infolytx Trainee Program.

Worked on PriyoGo to build people network graphTech stack: Django, Neo4j

In my role as a software engineer, I collaborated with a team consisting of both Swedish and Bangladeshi professionals to develop various data-driven products. Notably, we constructed a sophisticated recommender system that leverages historical and real-time behavioral patterns to recommend ads to users. Additionally, we integrated some Microservices with our ad serving engine and created the corresponding backend data infrastructure.To achieve our objectives, we utilised a range of cutting-edge technologies and tools such as S3, HBase, Spark, Hadoop, Redshift, and Hive. In terms of programming languages, we primarily employed Java, Scala, Python, and R.