Alip Kamate
junior data engineer
Jath, Sangli, Maharashtra
data engineer / data platform engineer
Alip Kamate
architect of intelligent data systems
transforming raw information into scalable intelligence.
python, sql, etl, warehouse modeling, airflow, spark, kafka, and analytics-ready datasets.
mapping raw data into trusted ledgers
about
profile summary
bca student focused on junior data engineering work: python ingestion scripts, sql transformations, data validation, warehouse-ready models, and clear documentation.
best fit
- junior data engineering teams that value clarity
- python and sql-heavy pipeline work
- data cleaning, validation, and warehouse-ready models
- open to junior data engineer and analytics engineer roles
education
bachelor of computer applications
Shivaji University, Kolhapur
currently pursuing
2021 - present
hsc science
Raje Ramrao College
secured 80.84%
2020
skills
python
ingestion scripts
sql
transformations
spark
scalable data
kafka
event streams
airflow
scheduling
docker
reproducible work
aws
cloud systems
machine learning
recommendation systems
more craft
pandas & numpy
postgresql
dbt
git & github
linux
etl and elt pipelines
warehouse modeling
data validation
projects
book recommendation system
scraped, cleaned, and transformed book metadata for recommendation features.
scrapypandasmachine learning
read case study
document search engine
local ingestion and indexing pipeline for documents, metadata, sqlite storage, and ranked retrieval.
pythonfastapisqlite
read case study
github
etl pipeline system
batch ingestion, staging, validation checks, marts, and bi-ready outputs.
airflowdbtpostgresql
kafka analytics platform
streaming design for event ingestion and near-real-time metrics.
kafkasparkdocker
machine learning recommendation engine
turning machine learning pipelines into reliable systems.
machine learningpythondata validation
experience
retail sales data pipeline
etl- built a batch ingestion flow for raw sales files and staged them into postgresql.
- modeled daily revenue, product, and customer marts with sql transformations.
- added validation checks for nulls, duplicates, and schema drift.
customer 360 analytics mart
warehouse- designed fact and dimension tables from customer, order, product, and support data.
- wrote tested sql models for retention, cohort, and activity reporting.
- documented metric definitions for consistent dashboards.
quick proof
- two linked case studies show source data, cleaning, storage, retrieval, and usable interfaces.
- hsc science: 80.84%
- github: github.com/kamatealip
- resume pdf available immediately