Charu Kulshrestha

Data Engineer

Noida, Uttar Pradesh, India5 yrs 5 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in designing scalable Azure Data Factory pipelines.
Proficient in optimizing Databricks notebooks with PySpark.
Strong foundation in CI/CD automation using Azure DevOps.

Stackforce AI infers this person is a Data Engineering specialist in the SaaS industry.

Contact

Skills

Core Skills

Data EngineeringMicrosoft AzureMetadata Management

Other Skills

ADFSADLARM templatesAgile MethodologiesAnalytical SkillsApache SparkAzure Data FactoryAzure DatabricksAzure DevOpsAzure DevOps ServicesBiomedical SciencesBiotechnologyCommunicationCustomer SatisfactionData Analysis

About

Graduated from JECRC University with a Bachelor of Applied Science in Biotechnology, transitioned into data engineer and is currently employed as a Data Engineer at Tata Consultancy Services. My expertise includes designing scalable Azure Data Factory pipelines and optimizing Databricks notebooks using PySpark and SQL for advanced data processing.I also specialize in creating metadata-driven frameworks and automation scripts for CI/CD pipelines using Azure DevOps. At Tata Consultancy Services, I contributed to developing RESTful APIs with FastAPI to enhance metadata services while improving pipeline orchestration. Working collaboratively, they supported the team in leveraging tools like Snowflake and Delta tables to optimize data solutions. Motivated by continuous learning and innovation, they bring a strong technical foundation and a proactive approach to solving complex data challenges in alignment with organizational goals.

Experience

5 yrs 5 mos

Total Experience

5 yrs 5 mos

Average Tenure

5 yrs 5 mos

Current Experience

Tata consultancy services

4 roles

Data Engineer

Promoted

Sep 2023 – Present · 2 yrs 9 mos

Designed and developed scalable Azure Data Factory (ADF) pipelines to orchestrate data ingestion, transformation, and loading from multiple structured and unstructured data sources.
Built and optimized Databricks notebooks using PySpark and SQL for large-scale data processing, cleansing, and transformation.
Created and maintained metadata-driven frameworks in SQL Server to enable dynamic pipeline executions, parameterization, and configuration management.
Developed deployment automation scripts using Azure DevOps (YAML pipelines/PowerShell/ARM templates) to support CI/CD for data pipelines and related artifacts.
Developed and maintained RESTful APIs using FastAPI to expose metadata services, trigger pipelines, and integrate with external systems securely and efficiently.

SQLADLData VisualizationData WarehousingMetadata ManagementData Engineering+11