Data Analytics Engineer with experience in ETL processes, data engineering, analytics tooling, and backend and machine learning work across startup and banking environments. Experienced with Databricks, SQL, PySpark, Pan…
Data Analytics Engineer with experience in ETL processes, data engineering, analytics tooling, and backend and machine learning work across startup and banking environments. Experienced with Databricks, SQL, PySpark, Pandas, Docker, Kubernetes, cloud platforms, and a range of databases and ML tools.
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Working Student at Impossible Cloud startup, working on making the data engineering and analytics tools from ground till deployment
Design and implementation of ETL processes on Databricks
Orchestrating the ingestion and transformation of data from diverse sources including Kafka, HubSpot, PostgreSQL, and Google Analytics
Using SQL, PySpark, and Pandas to develop robust pipelines to structure the data before loading it into Delta Lake
Generating analytics using Superset, Redash and Grafana for business and devs observability
Infrastructure for deploying and managing analytics tools utilizing Docker and Kubernetes on Amazon EC2
Orchestrating the setup and maintenance of containers to ensure the seamless operation of the analytics stack
Ideation, development and migration of metadata from Minio S3 bridge to CockroachDB for distributed architecture and faster application performance
Benchmarking different databases and on-prem cloud storage
Extensive use of Kubernetes to automate workflow interfaced with GitHub Actions
Worked closely with CTO, Senior Engineers and BizDevs to derive the data side of the startup's product
An year long trainee program where rotated in different banking groups and teams
Adapted to these roles and worked in differing teams getting diverse exposure to various engineering roles
End-to-End ML model implementation which pitches credit cards to customers based on bank’s transactional, historical and behavioral data
Used Python libraries such as scikit-learn, TensorFlow, SciPy etc.
Built REST API using Flask for model inference
Implemented and maintained bank’s data pipelines
Made ETL pipelines using Scala and Python (PySpark and pyHive)
Worked with SQL Server, Hive, and Hadoop databases
Used Bash scripting and extensive Linux server use for deployment, monitoring and logging ETL data
Worked as a backend engineer
Implemented and maintained features coded as REST API for core banking application using .NET Core and C#
Backend Engineer for a startup
Worked closely with CTO and engineering lead
Implemented different micro-services using JavaScript libraries such as Node.js and Express.js
Ticketing on Jira
Version control on Git/GitHub and communication on Slack
Deployed microservices on cloud using Docker
Used Kubernetes to orchestrate microservice
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