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Vidhyalakshmi varaprasad Bathina

@vidhyalakshmivarapra

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AI-powered data engineer building scalable real-time pipelines and lakehouses across AWS, Azure, and GCP.

United States

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What I'm looking for

I’m looking for a team where I can build scalable lakehouses and dimensional models, enforce data quality and governance, and partner with business stakeholders to deliver trustworthy metrics—ideally in regulated or analytics-driven environments.

Data Engineer | Azure & Databricks Certified | 5+ Years Building Enterprise Data Solutions

Experienced Data Engineer with a proven track record of designing and implementing scalable data solutions that drive business insights and operational efficiency. I specialize in building robust ETL/ELT pipelines, optimizing cloud data platforms, and ensuring data quality across enterprise environments.

Key Achievements:

Built 25+ production data pipelines supporting analytics and reporting for healthcare and enterprise clients
Successfully managed HIPAA-compliant data processing workflows, ensuring regulatory adherence
Led cross-functional data initiatives, translating business requirements into technical solutions
Optimized data platform performance resulting in improved processing efficiency and cost reduction

Core Expertise:

Cloud Platforms: Microsoft Azure (certified), AWS, GCP
Data Engineering: Python, SQL, PySpark, Databricks, Snowflake
Pipeline Tools: Azure Data Factory, ETL/ELT design, workflow orchestration
Visualization: Power BI, Tableau, dashboard development
Compliance: Healthcare data (HIPAA), enterprise security standards

Education & Certifications:

MS in Data Engineering
Microsoft Certified Azure Data Engineer Associate (DP-203)
Databricks Certified Data Engineer Professional

Currently seeking opportunities to leverage my expertise in building next-generation data platforms. I'm particularly interested in roles that combine technical challenge with business impact, where I can apply my experience in healthcare data, cloud architecture, and enterprise-scale solutions.

Status: Available immediately

Experience

Work history, roles, and key accomplishments

Current

Data Engineer

Current

Cardinal Health

Jan 2025 - Present (1 year 5 months)

Reduced new distribution source onboarding from 2 weeks to 5 days by building a parameterized ADF ingestion framework with linked service templates across
SAP, Blue Yonder, and internal OMS systems.

Azure Data Factory Databricks Delta Lake Pyspark SQL Tuning Data Quality PII Masking RBAC Power BI

Data Engineer

Foot Locker

Jul 2024 - Jan 2025 (6 months)

Integrated 5 source systems (POS, CRM, e-commerce, loyalty, inventory) into analytics pipelines using PySpark, Kafka, and Airflow with 98% accuracy. Designed a Snowflake/Redshift Customer 360 warehouse (12M+ records) and improved marketing/sales campaign analysis by 40% by implementing trusted KPI logic and ML-ready feature tables.

Pyspark Kafka Airflow Snowflake Redshift SQL Tuning

Data Engineer

Tata Consultancy Services

Jun 2020 - Jul 2022 (2 years 1 month)

Built ETL for 4+ banking and retail clients using Python, Spark, and SQL, processing 2TB+ daily and improving BI load times by 30% with 30+ Kimball-style fact/dimension tables. Automated ingestion from 10+ REST APIs and Kafka streams, reducing reporting time from days to hours, and tuned Spark/Hadoop jobs to cut runtimes by 35%.

Python Apache Spark SQL Data Warehousing Kafka REST APIs Spark Hadoop Optimization CI CD

Associate Data Engineer

Techcore

Aug 2019 - May 2020 (9 months)

Optimized 20+ SQL ETL pipelines across 3 legacy systems into PostgreSQL analytics datasets, improving accuracy by 30%. Built Kafka/Spark Streaming pipelines (100K+ events/day) with monitoring to reduce downtime by 25%, and set up Git/Jenkins CI/CD for environment promotion, cutting storage costs by 18%.