Data Engineer with 1+ years in ETL, SQL & Cloud Platforms
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Results-driven MCA graduate and Data Engineer with 2+ years of hands-on experience in building ETL pipelines, SQL engineering, BI analytics, and cloud-based data platforms. Proficient in PySpark, Azure Databricks, Delta Lake, SQL Server, and Power BI (Microsoft PL-300 Certified). Experienced across healthcare, e-commerce, and analytics domains. Seeking Data Engineer or Junior Data Engineer roles to contribute to scalable data infrastructure and pipeline development.
Annamacharya Institute of Technology & Sciences
Master of Computer Applications (MCA)
August 1, 2021 – October 1, 2023
Rayalaseema University
B.Com Computer Applications
August 1, 2018 – September 1, 2021
C2S Technologies
Data Engineer Intern
March 1, 2026 – June 1, 2026
India
Amazon
Catalog Data Specialist (Contract)
September 1, 2025 – January 1, 2026
India
AI VARIANT
Data Analyst Intern
May 1, 2024 – July 1, 2024
India
People Tech Group
Data Analyst Intern
December 1, 2023 – May 1, 2024
India
Healthcare Appointment & Pharmacy Management System
March 1, 2026 – April 1, 2026
Designed fully normalized relational database for healthcare platform managing patient appointments, prescriptions, medicine ordering, and billing Built 10+ stored procedures for patient registration, doctor search, appointment booking, and medicine stock validation Implemented triggers to auto-update medicine inventory on prescription creation and enforce business rules Validated 3 critical test cases: duplicate appointment prevention, slot conflict detection, and stock overflow handling
Automated Data Quality Framework
August 1, 2025 – October 1, 2025
Built a reusable PySpark-based data quality framework to validate schema compliance, null checks, range violations, and referential integrity across datasets Automated DQ summary reporting with results stored in Delta Lake tables and surfaced via SQL views for downstream consumption Reduced manual validation effort by 60% and improved data issue detection speed through automated pipeline monitoring Designed configurable rule engine — new datasets can be onboarded by simply adding YAML-based validation rules
View ProjectRetail Sales Data Pipeline – Medallion Architecture
January 1, 2025 – March 1, 2025
Designed and implemented a 3-layer Medallion Architecture (Bronze → Silver → Gold) on Azure Databricks to process retail sales data from multiple CSV/JSON sources Developed 10+ PySpark transformation notebooks for data cleaning, deduplication, aggregation, and business KPI computation across pipeline layers Used Delta Lake with ACID transactions, schema evolution, and Z-ordering to enable reliable incremental loads and time travel queries Built Power BI Gold-layer dashboards tracking sales trends, product performance, and regional revenue metrics using DAX measures Automated pipeline using Databricks Jobs scheduler with email alerts on failure
View ProjectElectric Vehicle (EV) Market Data Analysis
May 1, 2024 – July 1, 2024
Analyzed EV market trends and built interactive Power BI dashboards tracking adoption rate, regional penetration, and brand market share Designed relational data models and performed data cleaning to improve accuracy and reliability of insights Identified high-growth regions and future demand patterns through statistical analysis
Data Analyst Certification
ExcelR Solutions
June 1, 2026 – Present
Microsoft Certified: Power BI Data Analyst Associate (PL-300)
Microsoft
June 1, 2024 – Present
Cultural Fit Analysis
The candidate has experience across various domains (healthcare, e-commerce, EV market analysis) and project types (personal and professional), indicating adaptability and a broad interest in data challenges. The certifications and continuous learning (MCA degree) suggest a proactive approach to skill development. The target role of Data Engineer aligns well with the technical skills and project experience, particularly in pipeline development and data quality.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems, automate processes, and collaborate on data quality. The experience as a Catalog Data Specialist at Amazon suggests attention to detail and adherence to standards. However, the resume does not provide explicit examples of leadership, conflict resolution, or advanced problem-solving in a team context, which are crucial for senior roles.