pranoti patil

Data Engineer

Bengaluru, Karnataka, India 3+ yrs exp 87 · Excellent

About

Data Engineer with 3 years of hands-on experience building scalable data pipelines and performing data modeling for analytics use cases. Strong proficiency in SQL (complex queries, joins, aggregations), Python (PySpark, Pandas), and Big Data technologies (Hadoop ecosystem, Hive, Spark). Demonstrated expertise in data cleansing, transformation, validation, and implementing Star/Snowflake schema for data warehousing. Proven ability to collaborate with cross-functional teams to ensure high data quality and availability while maintaining version control scripts.

Skills & Expertise (33)

Python Advanced

8.1/10

Years Exp

PySpark Advanced

8.0/10

Years Exp

SQL Advanced

7.8/10

Years Exp

Apache Airflow Intermediate

7.5/10

Years Exp

AWS Glue Intermediate

7.5/10

Years Exp

Power BI Intermediate

7.0/10

Years Exp

AWS Redshift Intermediate

7.0/10

Years Exp

AWS S3 Intermediate

7.0/10

Years Exp

Data Validation Intermediate

7.0/10

Years Exp

Data Transformation Intermediate

7.0/10

Years Exp

Agile Practices Intermediate

6.5/10

Years Exp

Git Intermediate

6.5/10

Years Exp

Tableau Intermediate

6.5/10

Years Exp

AWS Athena Hadoop PyCharm HDFS Hive Apache Spark Snowflake GCP Azure AWS Lambda Dimension Tables AWS EC2 Databricks Delta Lake Star Schema Snowflake Schema Data Cleansing Pandas Shell Scripting Dimensional Modeling

Work Experience

Data Engineer

Dreamcare Developers

Jun 2023 - Present

Designed and developed scalable ETL/ELT data pipelines using PySpark, Python, and SQL on AWS, enabling efficient ingestion and transformation of large-scale datasets. Built and managed data pipeline orchestration using Apache Airflow, automating scheduling, monitoring, and dependency management for end-to-end workflows. Optimized complex Spark SQL queries, reducing job execution time by 40% through partition pruning, caching, and broadcast joins. Designed dimensional data models (Star schema) improving analytics query performance by 30%. Ensured data quality, governance, and security through validation frameworks, data checks, and controlled access mechanisms. Optimized cloud resource utilization and cost efficiency by tuning Spark jobs and implementing efficient storage strategies. Collaborated with cross-functional teams (data analysts, business stakeholders, product teams) to gather requirements and deliver scalable data solutions. Developed interactive dashboards using Power BI, enabling stakeholders to monitor KPIs such as customer churn and sales trends. Actively participated in Agile ceremonies, including sprint planning, stand-ups, and retrospectives, ensuring timely delivery.