• Working in the Data platform team which is the center for all Nextdoor data that can be stored and consumed for further analytics and intelligent decision making by applying machine leaning technologies.• Designing, setting up, and building the distributed platform for supporting all Nextdoor data. Work withanalytics engineering and data science teams to understand possible data pipelines efficiencies and provide automations for manual workflows.• Developing software systems using programming languages, frameworks and databases - Python, Java, Shell, Django, MySQL, No-SQL to build and set up the platform.• Following and ensuring best practices in software programs design and development by documenting standards and completing code reviews. Document the implementations and solutions in timely manner for technical and non-technical teams.• Set up and support data platform on AWS cloud (Amazon Web Services) and Databricks. Work on various AWS services like S3, EC2, ECR, ECS, RDS, terraform to create resources, docker containers.• Work on data batch processing tool like Airflow, Databricks workflows, notebooks, SQL endpoints.• Work on various distributed file system ecosystem tools and technologies like spark, hive, presto and other HDFS infrastructures to support different needs.

• Working in Data lake team which provides a central and efficient platform to producers and consumers of data. Data lake is built upon Hadoop distributed file system and supports spark, hive, Hbase and other HDFS infrastructure to support various actions. A central web service is also provided for easy interaction with the lake.• Working to solve and eradicating the problem of ingesting duplicate and similar data through multiple sources which is further leading to classification based on defined criteria.

• Set up the required environments for fast and efficient computing.• Accelerated towards solution by data cleaning, preprocessing and manipulation using python libraries like numpy, pandas, pyarrow etc.• Set up MLFlow for packaging the models , tracking , logging and deployment.

• Worked as a data science intern leveraging the ML and DL libraries like Keras, Tensorflow, Pytorch, scikitlearn etc.• Worked on time series data to design various prediction, forecasting and anomaly detection models and comparing them with respect to computing, optimization and performance. • Good hands on experience with data cleaning, preprocessing and manipulation using python libraries like numpy, pandas, pyarrow etc.

Worked as a Software Developer for Banking and Finance Project (Morgan Stanley) named Flexible Confirms which aims at the post trade processing. My core responsibilities were as follows:• 4+ years of experience as a software developer in both Agile & Scrum and Waterfall methodologies.• Worked with best practices of Software development lifecycle (SDLC) in finance domain (post trade technologies) backend application along with unit testing and TDD.• Continuous integration and deployment using Git and Jenkins.• Technologies: Core Java, Spring, Hibernate, Linux, Shell, SQL, Python• Tools & softwares: Junit, Perforce, Git, Crucible, Jira, eclipse, DBArtisan, Servicenow etc.

Worked as an Intern to develop a low cost computerized solution to serve as Cash Register know as POS (Point Of Sale)Terminal, which can be used to maintain sales and stock of items offered for sales.