Headline

Data Engineer | Python · SQL · Snowflake · AWS · ETL/ELT · Data Quality | Ex-Innovaccer | Immediate Joiner

About

I build production data pipelines that don’t break at 2 a.m. Around 1.5 years at Innovaccer, I’ve shipped and maintained 25+ ETL/ELT pipelines in Python and Snowflake, moving 50M+ records weekly across 40+ partner organizations on an enterprise healthcare data platform. My work is the unglamorous, high-stakes stuff data teams actually depend on: schema design, data quality frameworks, and cross-system validation that keeps reporting trustworthy. A few things I’m proud of: • Shipped a new client’s ingestion pipeline to production in one week, under SLA • Designed a Python + SQL reconciliation framework that hit ~95% match rate across 6 measurement categories • Built a data quality framework adopted across 6+ source systems, replacing manual QA cycles • Resolved 200+ data quality issues across 25+ production pipelines Beyond the code, I care about business impact — why a number is wrong, who it affects downstream, and how to stop it recurring. Outside work I’m deep into financial markets, value investing, and quantitative analysis: time-series forecasting on NSE equities (ARIMA/LSTM/XGBoost) and a credit-risk classifier (~79% accuracy). I’m especially drawn to roles where data engineering meets finance. Open to data engineering, analytics engineering, and fintech/quant data roles — NCR-based or remote, available immediately. Building a team that values someone who ships reliably and debugs deeply? Let’s talk → kunals7898@gmail.com

Location

Delhi

Work experience

Associate Data Engineer at Innovaccer, Jul 2025 - May 2026 · 11 mos, •Designed and developed scalable ETL pipelines ingesting nested JSON data from Amazon S3 into Snowflake across 8 entities; optimized data transformation workflows and resolved schema, normalization, and null-key issues in production environments •Built Python + SQL reconciliation framework for 40+ partner organizations; presented validation findings and match-rate trends to stakeholders, reducing escalations and enabling faster issue resolution •Built and scheduled automated data cleansing pipelines for L2 production tables, processing 5M+ records and improving downstream analytical data quality. •Built reusable data quality and validation frameworks with automated checks and HTML reporting, scaling across 6+ sites and reducing manual QA effort by ~80–90% •Monitored and maintained 25+ production data pipelines with 95%+ validation accuracy; troubleshot and resolved 200+ production and data quality issues to ensure data integrity and pipeline performance •Evaluated XML ingestion strategies; recommended Python (lxml/XPath) → CSV → Snowflake COPY INTO, improving performance and maintainability

Data Engineering Intern at Innovaccer, Jan 2025 - Jul 2025 · 7 mos, •Worked on production-grade Snowflake pipelines for 10+ healthcare source practices, ensuring reliable ingestion and transformation workflows •Built and integrated 5+ end-to-end data ingestion pipelines within medallion architecture (L0–L2), supporting scalable analytics and reporting use cases •Developed Accounts Receivable Basis (ARB) reports for Concerto client — synthesized cost and risk metrics into structured findings; output used by client managers for financial decision-making •Awarded Spot Award for consistently delivering high-quality solutions under tight deadlines

Summer Intern, Data Science at Celebal Technologies, May 2024 - Jul 2024 · 3 mos, Jaipur, Rajasthan, India, - Gained practical experience in data science by working on various mini-projects and assignments. - Developed strong skills in Python programming and successfully applied machine learning algorithms to real-world problems.

Education

Bachelor of Technology - BTech, Communication and Computer Engineering, The LNM Institute of Information Technology

Class XII, Science (PCM), Puna International School, Ahmedabad