Headline

Data Engineering | Physical AI | AI/ML | Ex-NBC Bearing | Ex- Accenture

About

I’m a data engineer who enjoys understanding how systems work and turning complex problems into reliable solutions. Over time, I learned that building a pipeline is only one part of the work. The real challenge is understanding why the data is needed, how it moves across the system, where it can fail, and how the solution can continue to work reliably in production. This way of thinking comes partly from my background in mechanical engineering, which taught me to look at systems as connected parts rather than isolated components. I carry the same mindset into data engineering by tracing problems to their root cause, keeping the overall architecture in view, and developing solutions from design through production. As AI becomes part of more businesses, I see strong data foundations as essential. I’m continuing to build my skills in data platforms that support analytics, machine learning, generative AI, and Physical AI. I’m interested in opportunities where I can take ownership, learn new domains, solve meaningful problems, and build solutions that create real business value.

Location

India

AI stack

claude code

codex

hugging face

langgraph

openai

Work experience

Data Engineer at National Engineering Industries Ltd. (NBC Bearings), Jul 2024 - Mar 2026 · 1 y 8 mo, India, • Worked on a hybrid data architecture, on-premises PostgreSQL database with Azure Data Lake Storage Gen2 (ADLS Gen2) and Azure Databricks for data processing and analytics. • Using PySpark, Python, SQL, FastAPI processing approx [90–100 GB] data per day. • Built ADF pipelines to ingest ERP, PostgreSQL, NoSQL, and IoT data into ADLS Gen2, improving production and machine data for downstream analytics. • Developed PySpark data-quality and transformation logic to detect duplicate events, missing machine IDs, abnormal sensor readings, and failed loads. • Improving the PostgreSQL star schema with fact and dimension tables for faster manufacturing KPI reporting and analytical results. (2 System Improvements Program). • Supported production pipelines, monitoring, debugging, CI/CD, and root-cause analysis. Project Work Brought a production dataset into a common Databricks pipeline for plant reporting. Built PySpark transformation and validation logic, resolved schema issues, and improved data flow for dashboards and analytics.

Application Developer at Accenture, Aug 2020 - Jun 2024 · 3 yrs 11 mos, Bengaluru, • Developed Oracle RMS ETL and data integration workflows using PL/SQL, SQL, Python scripting, REST API calls, and shell scripting. • Built Python utilities for validation, reconciliation, report generation, batch monitoring, and exception handling. • Supported Oracle RMS to WMS data movement with transformation, reconciliation, batch processing, and SLA-based availability. • Automated validation checks, reconciliation, monitoring, and log review, reducing manual effort by 20-30%. • Debugged production issues, optimized batch workflows, and reduced daily load time by 2-3 hours.

Summer Intern at HighRadius, May 2019 - Jun 2019 · 2 mos, Bhubaneswar

Summer Trainee at Tata Steel, May 2018 - May 2018 · 1 mo, KALINGA NAGAR ODISHA

Education

Master of Science, Computational Engineering, FAU Erlangen-Nürnberg

Bachelor of Technology - BTech, Mechanical Engineering, KIIT - Kalinga Institute of Industrial Technology