Rekha Ch
Data Engineer - Python, SQL • United States • c************@gmail.com • +14******714 • linkedin.com/•••••
Professional Summary
Data Engineer with 7 years of experience architecting ETL/ELT pipelines, cloud-native data platforms, and enterprise analytics solutions across finance, telecom, and technology domains. Specialized in Python, SQL, PySpark, Snowflake, AWS, Azure, Apache Spark, and Kafka for distributed data processing and real-time streaming operations. Accelerated ETL performance by 50% through pipeline optimization and scalable ingestion architectures. Engineered dimensional data models, cloud data lakes, and analytics-ready reporting layers supporting large-scale business intelligence operations. Automated governed data workflows using Airflow, AWS Glue, Azure Data Factory, and CI/CD pipelines to strengthen data lineage, reliability, and operational stability. Integrated REST APIs and enterprise data sources to deliver secure, high-performance analytics and reporting solutions.
Technical Skills
Programming Languages: Python
Libraries & Data Processing: Pandas,NumPy,PySpark
Big Data Technologies: Apache Spark,Apache Kafka,PySpark Structured Streaming
Cloud Platforms: AWS,Azure
Databases & Warehousing: SQL,Snowflake,Amazon Redshift,Azure Synapse Analytics
ETL & Data Orchestration: Apache Airflow,AWS Glue,Azure Data Factory,dbt
Modeling & Architecture: Scalable Data Architecture,System Design,Dimensional Modeling,Star Schema
Data Integration & APIs: REST APIs,Data Ingestion,OAuth,API Keys,Integration Patterns
Data Visualization Tools: Power BI,Tableau
Data Quality & Governance: Great Expectations,Data Security,Access Control,RBAC,Data Lineage
DevOps & Version Control: Docker,CI/CD,Git
Work Experience
Kestra Financial
Texas, USA
Data Engineer
Sep 2025 – Present
Tech Stack: ETL, ELT, Python, SQL, Snowflake, AWS, REST API, Data Ingestion, Data Validation, Data Reconciliation, Power BI, Tableau
- Engineered ETL/ELT pipelines using Python, SQL, Snowflake, and AWS services, improving data reliability and reducing reporting delays by 40%.
- Designed scalable REST API and enterprise data ingestion frameworks across analytics platforms, enabling secure and accurate data availability for business reporting.
- Optimized data validation and reconciliation processes by implementing automated quality checks, increasing data accuracy by 30% across critical reporting pipelines.
- Collaborated with cross-functional teams of analysts, developers, and business stakeholders to deliver enterprise-grade data solutions that improved operational decision-making efficiency.
- Developed automated KPI dashboards and reporting solutions using Power BI, Tableau, AWS S3 reducing manual reporting effort and improving business visibility.
Mastercard
New York, USA
Senior Data Engineer
Sep 2024 – Aug 2025
Tech Stack: ETL, Azure Databricks, PySpark, Apache Kafka, Delta Lake, Snowflake, Spark, Data Modeling, Python, SQL, CI/CD, Data Lineage, Monitoring Frameworks
- Orchestrated ETL pipelines and real-time streaming workflows using Azure Databricks, PySpark, Apache Kafka, and Delta Lake, reducing data processing latency by 25%.
- Constructed scalable dimensional data models and Snowflake reporting layers supporting enterprise analytics, KPI tracking, and high-volume business reporting operations.
- Revamped Spark transformation workflows and partitioning strategies to eliminate distributed processing bottlenecks, increasing pipeline throughput and processing efficiency.
- Coordinated with analytics, product, and business stakeholders across enterprise reporting initiatives, accelerating delivery of scalable and analytics-ready data solutions.
- Automated governed data pipelines and monitoring frameworks using Python, SQL, and CI/CD , strengthening data lineage, reliability, and operational performance.
AT&T
Texas, USA
Data Engineer
Jun 2022 – Aug 2024
Tech Stack: AWS S3, Redshift, Snowflake, ETL, ELT, AWS Glue, AWS Lambda, Python, PySpark, SQL, Data Lake, Data Warehouse, Cloud Storage, Monitoring
- Modernized enterprise data lake and warehouse ecosystems using AWS S3, Redshift, and Snowflake, reducing ETL processing time across analytics workloads.
- Deployed automated ETL/ELT workflows using AWS Glue, AWS Lambda, Python, and PySpark to support scalable telecom reporting and analytics operations.
- Streamlined complex SQL queries and data models by optimizing transformation logic and storage processes, improving reporting performance and query efficiency.
- Partnered with cross-functional engineering and analytics teams to deliver scalable cloud-based data solutions aligned with enterprise business requirements.
- Reinforced pipeline scalability and operational reliability through proactive monitoring, performance tuning, and cloud storage optimization using AWS and Snowflake technologies.
Neudesic
Hyderabad, India
Data Engineer
Dec 2020 – Sep 2021
Tech Stack: Azure Data Factory, Azure Synapse, SQL, Python, ETL, FastAPI, Azure Data Lake, Data Modeling, Real-Time Data Access
- Consolidated enterprise reporting pipelines using Azure Data Factory and Azure Synapse, improving analytics processing efficiency and accelerating data availability.
- Formulated data models and SQL transformation logic for BI workloads, increasing query performance by 30% across reporting systems.
- Automated repetitive data processing tasks using Python-based workflow solutions, reducing manual intervention and improving operational efficiency.
- Collaborated with engineering and reporting teams to deliver scalable ETL solutions supporting enterprise analytics and business reporting initiatives.
- Integrated FastAPI-driven data services with Azure Data Lake and ETL frameworks, enabling secure real-time data access and streamlined reporting operations.
Mulya Technologies
Hyderabad, India
Python Developer
Jan 2019 – Dec 2020
Tech Stack: Python, SQL, ETL, Data Ingestion, REST APIs, Flask, MongoDB, Data Integration, Backend Integration, API-Driven Services
- Delivered ETL pipelines and automated data ingestion scripts using Python and SQL, improving data processing efficiency and reporting reliability.
- Engineered REST APIs and backend integration services using Flask and MongoDB to support secure and efficient cross-system data exchange.
- Refined complex SQL queries and database operations to eliminate reporting delays, accelerating query performance and data retrieval speed.
- Supported development initiatives with engineering and application teams to implement scalable backend solutions aligned with business requirements.
- Configured data integration workflows and API-driven services using Python, Flask, MongoDB, and ETL frameworks, strengthening application performance and automation efficiency.
Education
New England College
Master of Science in Computer and Information Systems • Henniker, USA • Jan 2022 – May 2023
Dhanekula Institute of Engineering and Technology
Bachelor of Technology in Electronics and Communication Engineering • India • Aug 2014 – May 2019
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