Ankit Yadav 🇮🇳

Data Scientist

Delhi, India4 yrs 10 mos experience

Highly Stable

Key Highlights

4+ years of experience in data engineering.
Expert in Azure Data Engineering and cloud technologies.
Skilled in developing efficient data-driven solutions.

Stackforce AI infers this person is a Data Engineering expert specializing in cloud-based solutions and scalable data processing.

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Skills

Core Skills

Data EngineeringAzure DatabricksMicrosoft Azure

Other Skills

Azure Data FactoryAzure DevOpsAzure Synapse AnalyticsDatabase Management System (DBMS)GitPySparkSQL

About

I’m Ankit Yadav, dedicated data engineer with over 4+ years of experience in cloud-based big data processing and analytics, skilled in developing data-driven solutions. Utilizing technologies such as PySpark, SQL, Python, DataBricks. Ankit's expertise lies in cloud technologies, and he is particularly enthusiastic about leveraging the power of cloud platforms for efficient and scalable data solutions. With a focus on Azure, Ankit has gained substantial experience as an Azure Data Engineer, designing and implementing robust data pipelines and analytics solutions. As a skilled programmer, Ankit enjoys coding in Python and Terraform, utilizing these languages to develop effective and efficient solutions. He keeps up with the latest advancements in cloud technology and programming techniques to ensure he can deliver the best results. With a strong foundation in cloud technology, programming, and Azure Data Engineering, Ankit is well-equipped to drive innovation and success in the ever-evolving field of data engineering. His passion for learning and dedication to excellence make him a valuable asset to any team or project.

Experience

Pwc

Senior Data Engineer

Jun 2025 – Present · 9 mos · Gurugram, Haryana, India · Hybrid

Implemented end-to-end ETL processes using Azure Data Factory, Azure Databricks with PySpark, and Azure Synapse Analytics, resulting in a 40% reduction in data processing time and improved data accuracy.
Created requirement-specific logic in Azure Databricks using Spark SQL and PySpark, leveraging Medallion architecture, to process the data from Azure Data Lake Storage Gen2 or Manual Excel files, and orchestrated pipelines in Azure Data Factory.
Cleansed data on the bronze layer by handling missing values, duplicates, and standardizing formats, then loaded refined data into the silver table for advanced analysis and reporting.

Azure Data FactoryAzure DatabricksPySparkAzure Synapse AnalyticsData Engineering

Deloitte

Data Engineer

Apr 2022 – Jun 2025 · 3 yrs 2 mos · Delhi, India · Remote

Designed and maintained scalable ETL/ELT pipelines using PySpark and SQL to process large volumes of vehicle sensor data, delivering actionable insights into vehicle health for strategic decision-making
Leveraged Microsoft Azure’s cloud-based aggregation platform to ingest, transform, and store multi-source vehicle data for seamless API marketplace integration.
Led the complete ETL integration for Construction API data, managing ingestion from diverse formats including JSON and XML.
Built reusable, object-oriented Python modules for ETL processes, enabling scalable and maintainable data solutions.
Implemented robust data validation frameworks using Apache Spark, significantly improving data quality and workflow reliability.

PySparkSQLMicrosoft AzureData Engineering