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Deepmita Ray

@deepmitaray

Message

I build reliable Azure data pipelines, ETL workflows, and business-ready analytics at scale.

India

Message

At Ernst & Young, I engineer Databricks-based ETL workflows and automated quality checks for 200+ daily and monthly files, sustaining 98.6% processing uptime while reducing errors by 30%.

I build transformation logic with PySpark and Spark SQL, onboard new fund files through UAT and production, and improve Power BI reporting reliability for business stakeholders.

Previously at Techspian, I designed scalable data pipelines, transformation workflows, and RESTful APIs using Python, PySpark, SQL, and Databricks. My work improved ingestion efficiency by 25% and reduced manual processing effort by 20%.

I also bring data science experience from Rubixe and Idow, where I built machine-learning pipelines and predictive models, analyzed large datasets, and turned results into dashboards and actionable insights.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Ernst & Young

Jul 2024 - Present (2 years 2 months)

Automated data validation and quality checks, achieving 98.6% processing uptime and reducing errors by 30%. Engineered and optimized 15+ ETL workflows using Databricks, PySpark, and Spark SQL, and improved Power BI reporting reliability by 25%.

Databricks PySpark Spark SQL Power BI ETL Data Validation Data Quality Azure Data Factory ADLS SQL

Data Scientist

Rubixe

Mar 2023 - Dec 2023 (9 months)

Processed 1M+ records from APIs, databases, and web sources by developing reusable preprocessing and feature-engineering pipelines, reducing data preparation time by 30%. Developed and evaluated 5+ machine learning models for predictive analytics and recommendation systems, achieving 85%+ accuracy.

Python Machine Learning data preprocessing Feature Engineering Predictive Analytics Recommendation Systems Dashboarding Data Visualization

Associate Software Engineer

Techspian

Mar 2022 - Feb 2023 (11 months)

Designed and configured 10+ scalable ETL and data pipelines using PySpark, Python, and SQL, improving data ingestion efficiency by 25%. Built 5+ data transformation workflows and RESTful APIs integrated with Databricks pipelines.

PySpark Python SQL ETL REST APIs Databricks Data Pipelines

Python Developer

Idow

Oct 2021 - Feb 2022 (4 months)

Analyzed 500K+ data records using Python, Pandas, SciPy, and Seaborn, performing EDA and statistical hypothesis testing to identify trends and insights. Conducted 20+ ML experiments and A/B tests using MLflow, Scikit-learn, and Jupyter Notebooks.