Hello Data Enthusiasts,

I am Sumit Mittal (Founder @ Trendytech.in), offering In-depth Big Data on Cloud & GenAI Trainings.

An NIT Trichy alumnus, I have worked with Top companies like Cisco & VMware before starting Trendytech.

My passion towards transforming lives of students, made me able to train:
- 30,000+ IT Professionals
- Working at Top Product based Companies like Microsoft, Walmart, Google, VISA, Mastercard and more

My structured way of preparing, ensures to give you exposure equivalent to a 4+ years actually experienced Data Engineering professional.

I have empowered Individuals to Transition & Grow Exponentially, through my below most popular programs:
-  Ultimate Data Engineering Program
-  Gen-AI Masters Program

Entire curriculum is designed basis industry requirement, covering most important tech stack like:
- Pyspark, Databricks, Data Factory, AWS Cloud Services, Data Modeling, System Design & a lot more
- Agentic AI, RAG, LangChain, Prompt Engineering and more

Do Visit my Website https://trendytech.in/ for more details

Sumit Mittal

Optum

•	Cloud Migration Project:
o	Successfully migrated data pipelines from IBM Datastage on-premises to Azure cloud (Airflow, ADF, Databricks). This transition improved scalability and reduced maintenance costs. 
o	Functionally tested migrated code (external vendor tool) for data pipelines in Databricks notebooks.
o	Designed and developed additional modules in Azure Data Factory (ADF) and Databricks to create data pipelines in cloud.

•	Healthcare Economics:
o	Designed and developed complex data solutions using Airflow, ADF, Databricks, Snowflake, and GitHub to empower healthcare business users with valuable insights.
o	Orchestrated and scheduled data pipelines using Apache Airflow with Directed Acyclic Graphs (DAGs) to trigger tasks in ADF pipelines, Databricks notebooks, workflows, and data access from ADLS gen2/BLOB storage.
o	Designed and built Azure Data Factory (ADF) pipelines for data extraction, transformation, and loading (ETL) from various sources like Snowfake, SQL Server, NAS drives (zip, text, CSV files), and loading data to Databricks Delta tables or performing CRUD operations.
o	Leveraging Databricks notebooks, we implemented the medallion architecture (bronze, silver, gold) to ensure data quality and progressive data refinement for healthcare business users. Transformed raw data into increasingly structured and refined layers, culminating in curated data optimized for reporting and analysis in Snowflake.
o	Loaded curated data from Databricks gold layer tables to Snowflake for business intelligence and advanced analytics using star schema-based data models.
o	Utilized GitHub for version control and GitHub Actions for code deployment across Airflow, ADF, and Databricks environments.

Data Analyst

Infosys

1. Working on data ingestion from source systems with semi-structured data, structured data, time series data using ADF and migrating to Azure Data Lake, Azure Databricks and SQL Data warehouse.

2. Created and maintained data pipelines for ADF and Databricks, ingesting data across 5 disparate source.

Technologies used:
Python, SQL, Azure Data Factory, Azure Databricks, Azure Logic App, Azure DevOps, Azure SQL (SSMS)

Senior Associate Consultant

1. Working in data engineering team for a Oil and gas major, helping in ingesting and analyzing millions of data using Azure services.

2. Working on data ingestion from source systems with semi-structured data, structured data, time series data using ADF and migrating to Azure Data Lake, Azure Databricks and SQL Data warehouse.

Technologies used:
Python, SQL, Azure Data Factory, Azure Databricks, Azure Logic App, Azure DevOps, Azure SQL (SSMS)

Associate Consultant

1. Data ingestion from sources like Sql server, Oracle, files (XLSX, CSV).

2. Enhanced and supported data pipelines in ADF, Azure Databricks.

Technologies used:
Azure Data Factory, Azure Databricks, Azure SQL (SSMS)

Associate Business Analyst

1. Data ingestion from files (XLSX,CSV) which contains the data from PI AF into Azure data lake for different regions.  
2. Worked on the development of various process screens in PI vision and PI Processbook, to visualize near real time and time series data.

Technologies used:
SQL, Python, Azure Data Factory, Azure data lake, Azure Databricks, OSIsoft PI Vision, PI Processbook, PI Datalink,

Senior System Engineer

1. Worked on the development of 100+ process screens in PI Vision for a oil and gas super major.

2. Developed PI AF analysis for OSIsoft PI based application used for chemical injection and inventory management.

Technologies used: 
OSIsoft PI Vision, PI AF, PI Datalink

Systems Engineer

Intern in the infosys internship programme, 2018. Trained in Python, DBMS, C#, .net.

Intern

Seasoned Data Engineer with a demonstrated history of working in the IT industry. 

Skilled in Python, PySpark/Spark, SQL, ETL, ELT, Azure Data Factory, Azure Databricks, Apache Airflow, GitHub, GitHub Actions, Azure Data Lake storage Gen2 , Delta Lake, Lakehouse, Azure DevOps, Logic Apps, Azure SQL(SSMS), Big Data.

Strong information technology professional with a Bachelor's degree focused in Computer Science and Engineering with specialization in Cloud Computing and Virtualization.

taplio

The Battle

Sumit Mittal

ARPIT TAPWAL

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