Pragya P.

Pragya P.

Indore, India
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About Me

Pragya is a Data Engineer with 5+ years of experience designing and maintaining scalable data pipelines and cloud-based data architectures using Python, SQL, and relational databases (PostgreSQL, MSSQL, Oracle), with deep understanding of data modeling and transformation. She has strong hands-on experience with AWS Cloud Services (S3, Glue, Redshift, Lambda, Athena) for large-scale data processing and proficiency in ETL/ELT development, query optimization, and orchestration using Airflow and DBT. Pragya has worked with structured and unstructured data, applying advanced data validation and transformation logic, leveraging ORMs (SQLAlchemy), OOP principles, and Python performance optimization.

AI, ML & LLM

AI/ML Apache Airflow

Backend

Python REST APIs Django

Database

MySQL PostgreSQL SQLAlchemy MSSQL SQL DBT Oracle

DevOps

Azure Docker Cloud Functions Terraform CloudWatch GCP CI/CD Pipelines EC2 Prometheus AWS

Workflow

Git GitHub Actions GitLab CI

Other

Data Modeling Functional programming Regex Redshift BigQuery Caching Informatica Lambda Numpy Query Optimization Athena DataDog Matillion RabbitMQ Kinesis Prefect IAM Kafka Partitioning Talend Clustering Data Governance Data pipelines Dimensional Modeling Pandas Performance Tuning Quicksight S3 Data Engineering Data Transformation Multiprocessing Snowflake Agile

Work history

UpStack
UpStack
Data Engineer
2025 - Present
Remote

  • Developed a centralized analytics platform that enables real-time business insights by integrating multiple data sources into a unified warehouse.

  • Designed and deployed scalable ETL pipelines using AWS Glue and Airflow for data ingestion and transformation.

  • Built data validation layers and batch jobs using Python and AWS Batch.

  • Implemented optimized schemas in Redshift and automated query tuning for improved performance.

  • Integrated unstructured datasets and transformed them into analytics-ready tables.

  • Developed Terraform scripts for provisioning AWS infrastructure components.

  • Collaborating with data scientists to deliver curated datasets for AI/ML use cases.

PythonSQLAlchemyAWS GlueRedshiftLambdaAthenaAirflowDockerTerraformAWS Batch AI/ML ETL Pipelines
ZecData Technology
ZecData Technology
Data Engineer
2023 - 2024 (1 year)
Indore, India

  • Developed Databridge, a unified integration system for migrating enterprise data from legacy systems to cloud data warehouses.

  • Built ETL workflows to ingest and transform large datasets from Oracle and Salesforce into AWS Redshift.

  • Used Pandas and NumPy for complex data transformation and cleansing operations.

PythonDBTPostgreSQLPandasNumpyAWS S3LambdaRedshiftDockerData Transformation Data Cleansing
Accenture
Accenture
Associate Data Engineer
2021 - 2022 (1 year)
Bangalore, India

  • Developed and optimized SQL queries for data extraction, aggregation, and reporting.

  • Created and maintained ETL scripts in Python to automate data refresh cycles.

  • Collaborated with analysts to deliver clean, structured data for visualization tools.

PythonSQLOracleMSSQLAWS EC2S3PandasETLPerformance Tuning AWS

Showcase

Zid
Zid

Maintained MySQL and Redshift schemas, executing Redshift SQL tuning for large analytical queries. Developed ELT workflows using DBT and automated deployments using Terraform. Designed and deployed AWS Lambda jobs to support real-time ingestion and alerting. Managed Docker image creation for deployment and integrated Quicksight dashboards for BI. Used S3 for storing staging data and implemented retention policies to optimize storage. Built user interfaces with Django to provide insights and allow ETL triggering via web UI. Tech stack: Python, AWS Redshift, DBT, MySQL, Terraform, Lambda, ECR, EC2, S3, Quicksight, Django.

Education

BCA
BCA
IES College of Technology Bhopal - India
2017 - 2020 (3 years)