Nallandhighal Sai Rahul

Data Engineer

Hyderabad, Telangana, India3 yrs 5 mos experience

Most Likely To Switch

Key Highlights

Built a robust data quality framework with 65 validation rules.
Achieved 90% accuracy in customer churn prediction.
Specialized in cloud-based data processing across AWS and Azure.

Stackforce AI infers this person is a Data Engineer specializing in cloud-based data processing and ETL pipelines.

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Skills

Core Skills

Data EngineeringEtl PipelinesData Science

Other Skills

PySparkAWSSQLAzure Data LakePythonPandasCore JavaData PreparationC++MatplotlibSeabornExtract, Transform, Load (ETL)Amazon Web Services (AWS)Azure Data FactoryTensorFlow

About

Data Engineer with 2 years of experience building production-grade data validation, ingestion, and transformation pipelines for regulatory and accreditation use cases. Specialized in metadata-driven frameworks, Python automation, and cloud-based data processing across AWS and Azure. Proven ability to reduce manual validation effort, improve data reliability, and deliver analytics-ready datasets used by downstream reporting and compliance teams.

Experience

3 yrs 5 mos

Total Experience

1 yr 9 mos

Average Tenure

1 yr 11 mos

Current Experience

Ust

2 roles

Associate Data Engineer

Jul 2024 – Present · 1 yr 11 mos

Built and extended metadata-driven data quality framework with ~65 validation rules across large-scale datasets.
Developed and maintained Spark-based ETL pipelines for ingestion, transformation, and validation of structured datasets
Improved data reliability and reduced manual validation effort through automated rule-based checks
Worked on cloud-based data processing using AWS services (Glue, S3, Athena)
Built SQL-based data validation checks improving reporting accuracy
Automated data analysis workflows using Python (Pandas)
Supported analytics use cases for regulatory and accreditation reporting

PySparkAWSSQLAzure Data LakeData EngineeringETL Pipelines

Internship Trainee

Apr 2024 – Aug 2024 · 4 mos

SQLCore Java

Aiml analytics

Data Science Intern

Jan 2023 – Aug 2024 · 1 yr 7 mos

Developed a robust Customer Churn Prediction System utilizing a dataset comprising 10,000 records, employing advanced techniques in data preprocessing and model development
Conducted comprehensive exploratory data analysis (EDA) using visualizations with Matplotlib and Seaborn to gain insights into the dataset’s characteristics and distributions
Documented innovative methodologies, data analysis results, and actionable insights from the customer churn prediction project; enhanced organizational knowledge sharing and inspired future research initiatives in the customer relationship management sector
Obtained an accuracy of 90 percent during testing.

Data PreparationC++Data Science