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