ClanX is hiring a Data Engineer Intern to work on production-grade data pipelines, data modeling, and analytics systems that power enterprise AI solutions for industrial equipment monitoring and predictive maintenance.
Company Details
This is an enterprise AI company building real-time monitoring, diagnostics, and predictive maintenance solutions for industrial equipment. The company serves clients across oil & gas, power generation, and LNG sectors through production-grade AI and physics-informed machine learning systems.
Requirements
Pursuing or recently completed a degree in Computer Science, Engineering, Mathematics, or a related field
Strong SQL fundamentals including joins, aggregations, CTEs, and window functions
Good Python programming skills with experience using Pandas, Polars, or similar libraries
Understanding of ETL/ELT, data modeling, batch processing, and pipeline fundamentals
Experience working on at least one data-focused project, internship, research project, or coursework
Familiarity with Git and collaborative development workflows
Strong problem-solving and analytical thinking skills
Eagerness to learn and work in a fast-paced startup environment
Responsibilities
Build and maintain batch ETL/ELT pipelines for sensor and operational data
Develop data transformations using Python, SQL, and data processing frameworks
Assist in modeling and organizing time-series datasets for analytics and machine learning use cases
Support ingestion of client data into the company’s lakehouse platform
Implement data validation, freshness checks, and quality monitoring
Contribute to datasets used by ML feature pipelines and business analytics
Debug, test, and improve pipeline reliability and performance
Collaborate with Data Engineers, ML Engineers, and Product teams on production systems
Gurugram — Hybrid (2–3 days on-site)
Interview Process
SQL & Python Assessment
Technical Discussion
Culture Fit Round

ClanX brings world-class product builders together as cloud-based teams and connects them with companies that have meaningful product missions.