Profile

Agile Data engineer with 2+ years of experience designing and shipping end-to-end data platforms, ETL pipelines, and cloud/​data warehouse solutions in telecom and utilities. Skilled at translating business requirements into robust data models and automated workflows using Python, SQL, Airflow, Snowflake/​PostgreSQL, and LLM‑powered AI agents to power analytics, BI, and operational reporting.

Education
University at Buffalo, Masters In Data science
08/2024 – 12/2025 | Buffalo,NY
Professional Experience
08/2025 – Present | Buffalo,USA
  • •Built an end-to-end utility bill ETL and audit platform using Python, Apache Airflow, n8n, PostgreSQL (hosted on Heroku), AWS S3, and LLM agents to ingest, normalize, and validate high-volume billing data.
  • •Integrated cloud storage (AWS S3) for scalable data ingestion and archival, improving data accessibility and version control for audit workflows.
  • •Designed pipelines that cut manual review time by 60%, scaled analysis to 1,000+ bills/​month, and improved data quality for downstream BI and reporting.
  • •Developed a Streamlit-based audit console and modular DAGs, enabling configuration-based onboarding for new utilities, tariffs, and audit rules without code rewrites.
  • •Collaborated with auditors and business leaders to refine data models, thresholds, and exception categories, aligning audit logic with real-world billing workflows.
    • 09/2022 – 07/2024 | New Mumbai,India
  • •Led end‑to‑end development of a data platform (.NET, Python, MySQL, Camunda) that automated the FTTX deployment lifecycle and eliminated spreadsheet‑based workflows.​
  • •Designed and operated ETL jobs ingesting and cleaning 100K+ daily GIS and log records into a centralized MySQL store for reporting and downstream tools.
  • •Optimized schemas and queries for analytics workloads, improving query performance by 20%, and exposed structured deployment and financial data via RESTful APIs while collaborating with planning, finance, and field teams to define critical fields, validations, and reports that removed deployment and cost bottlenecks
    • Skills
    Programming & Scripting: Python, SQL, R, C#, Bash
    Data Engineering: Apache Airflow, Kafka, PySpark, n8n, ETL/ELT, data modeling, data quality, data warehousing
    Cloud & DevOps: AWS (S3, EC2 ,RDS), Azure, Docker, Terraform, CI/CD pipelines
    Data Platforms: Snowflake, PostgreSQL, MySQL, SQL Server, cloud data warehouses
    Analytics & BI: Power BI, Tableau, dashboard development
    Development Tools: Git, GitHub, FastAPI, .NET, APIs(FastAPI, REST)
    Professional Skills: Stakeholder communication, Technical leadership, Problem-solving, Documentation, Ownership
    Projects
  • •Built a cloud-native EV charging data warehouse on Snowflake using dimensional modeling and ELT pipelines to centralize station, session, and customer usage data for analytics at scale.
  • •​Enabled self-service performance dashboards and SQL-based reporting so stakeholders could analyze utilization, load patterns, and capacity needs, improving data-driven planning for expanding EV charging networks.
  • •Built a multi-agent AI utility billing platform using LLM APIs, Apache Airflow, FastAPI, PostgreSQL, n8n, and Streamlit to automate end-to-end bill ingestion, tariff reconciliation, and anomaly detection for high-volume invoices.​
  • •Eliminated most manual reconciliation work, surfaced real-time overcharge and discrepancy alerts by comparing bills against official tariffs, and cut audit cycles from weeks to hours while improving detection accuracy
  • •Built a full-stack real-time analytics pipeline using Apache Kafka and Python to stream, process, and visualize live e-commerce events such as clicks and cart additions for user journey monitoring.​
  • •Delivered sub-second visibility into drop-offs, abandoned carts, and conversion bottlenecks, enabling rapid A/​B testing decisions on funnels while handling thousands of user events per second.