PRATEEK KHARWAR
Data EngineerAI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Data Engineer with less than a year in SQL & Python.
Currently pursuing a Bachelor of Technology in Production and Industrial Engineering, I am an aspiring Data Engineer with a strong foundation in SQL, Python, and data pipeline orchestration tools like Apache Airflow. My internship as a Data Analyst and various projects in data engineering and warehousing demonstrate my ability to conduct end-to-end data analysis, build automated ELT pipelines, and design robust data architectures. I am passionate about leveraging data to drive actionable insights and build production-grade solutions.
Indian Institute of Technology Roorkee
B.Tech · Production and Industrial
August 1, 2021 – June 30, 2025
Happy Model School, Varanasi
CBSE (X)
N/A – May 31, 2019
Central Hindu Boys School BHU School, Varanasi
CBSE (XII)
N/A – May 31, 2021
CodeAlpha
Data Analyst Intern
May 1, 2026 – June 1, 2026
India
Automated Weather Data Engineering Platform
June 1, 2026 – June 1, 2026
Engineered a fully automated hourly ELT pipeline ingesting weather data for 10 Indian cities via OpenWeatherMap API built a 5-task Airflow DAG with parallel extraction, XCom quality gates, and exponential-backoff retry; landed raw JSON to a Hive-partitioned local data lake (city/year/month/day/hour) and batch-loaded 9,000 rows/day into Google BigQuery using the Jobs API (free-tier compatible, replacing streaming inserts). Implemented a medallion-style dbt transformation layer with 6 SQL models across 3 BigQuery datasets - staging views (type-cast, rename, null-coalesce), an intermediate join model (latest current conditions - 24h forecast by city), and 3 mart tables (daily aggregates, city comparison with temperature ranking, 24h forecast) with day partitioning + city clustering, 20 automated data tests, and a custom generic test macro serving a live Looker Studio dashboard. Delivered a full observability and reliability layer: a pipeline_health_check.py script performing 7-stage data lineage checks (raw files → BQ raw → stg → mart) with per-date city-level gap detection and auto-generated fix commands; a 4-job GitHub Actions CI pipeline (lint + 13 unit tests + dbt compile + Docker validate) on every push; - production-grade reliability patterns on a zero-cost infrastructure stack.
View ProjectEnd-to-End Data Warehouse
January 1, 2026 – February 1, 2026
Design a 3-tier medallion architecture (Bronze/Silver/Gold) on SQL Server, consolidating 6+ raw CSV datasets from 2 source systems (ERP & CRM) with end-to-end ETL pipelines - reducing data inconsistencies to zero before loading into the Silver layer. Engineered a star schema with 1 fact table and 4+ dimension tables, enabling optimized analytical querying across customer behavior, product performance, and sales trends. Delivered a multi-page interactive dashboard with 5+ KPI cards, trend line charts, categorylevel drill-downs, and dynamic slicers, translating warehouse data into actionable business insights for strategic decision-making. — GitHub (PowerBI)
View ProjectAdvanced Valuation and Strategy - M&A, Private Equity, and Venture Capital
Erasmus University Rotterdam
June 1, 2026 – Present
Intermediate SQL
HackerRank
June 1, 2026 – Present
Wealth and Personal Banking Virtual Experience
HSBC
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in data engineering, aligning well with a target role in this field. The diversity of projects, from weather data ELT to a general data warehouse, shows a breadth of application. However, the experience is primarily academic and personal projects, with only one brief internship as a Data Analyst. This indicates a strong learning curve and self-starter attitude, which can be a good cultural fit for dynamic environments, but also suggests a need for mentorship in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on delivering robust, production-grade solutions, even in personal projects. The emphasis on observability, reliability, and automated testing suggests a strong operational mindset. While direct team collaboration experience in data engineering is limited to personal projects, the detailed project descriptions imply an organized and thorough work ethic.