Mohammed Kashif

• Responsible for designing and maintaining APIs/Data Pipelines for ingesting data into our Machine Learning models (FastAPI, Python, AsyncIO, Dask, Azure, MLFlow, Docker, PostgresSQL).
• Created tools and dashboards to monitor data ingestion pipelines for our customers. • Used MLFlow fortracking and serving models for different customers.
• Streamlined end-to-end Operations forimproved customer experience.
• Migrated our services from on-prem to Azure, which involved re-writing the deployment/monitoring scripts.
• Migrated CI/CD framework from Jenkins to Github Actions using pants.
• Mentorjunior engineers towards implementing efficient and clean code.

• Worked as a Data Engineer, and helped in setting up Apache Airflow DAGs for data ingestion and processing (using Pyspark).
• Responsible for end-to-end design and optimization of Airflow DAGs.
• Creating Dashboards for visualizing Streaming data using Apache Kafka
• Migrated cloud infrastructure from AWS to Microsoft Azure

• Managing the complete data pipeline for ingestion and processing
• Research new healthcare datasets to be ingested into the pipeline
• Responsible for reducing the turnaround time for new dataset ingestion and
processing.
• Optimize the data ingestion process to utilize resources in the most efficient
manner possible.
• Identify places where code redundancy can be reduced as much as possible.
• Also part of the team to mentor interns for Python.

Used Python, Apache Airflow, Pandas, NetworkX