Apprentice, IT Development Program

TalentD; Pune District; On-site; INR 240,000 - 420,000; Full time

Job summary

Eaton is seeking an Apprentice to join the Master Data Management (MDM) team in Pune. You will work closely with senior data engineers to support data engineering, quality, and governance initiatives while building foundational skills in enterprise data management.

You will gain hands-on experience with Snowflake, data architecture, Medallion Architecture, and GenAI capabilities in a collaborative, learning-focused environment.

Qualifications

• Bachelor's degree in CS/IT/Data Engineering or related field
• Hands-on academic or project experience in data-related domains
• Basic understanding of SQL and data warehousing concepts

Responsibilities

• Support development and maintenance of MDM solutions on modern cloud platforms (Snowflake preferred)
• Assist in implementing Medallion Architecture (Bronze, Silver, Gold layers) for structured data processing
• Write and optimize SQL queries for data transformation, validation, and analysis
• Take part in data modeling and data architecture discussions
• Support data quality, cleansing, and standardization initiatives
• Assist in building data pipelines, Streamlit apps, and workflows
• Explore and prototype GenAI-driven use cases in data management
• Collaborate with cross-functional teams, including data stewards, business stakeholders, and engineering teams
• Document technical designs, transformations, and best practices

Skills

SQL basics

Data warehousing concepts

Snowflake knowledge

Data architecture fundamentals

Medallion Architecture

GenAI concepts

ETL/ELT exposure

Snowflake Certification

Academic/project data experience

Education

Bachelor's degree in Computer Science, Information Technology, Data Engineering, or related field

Tools

Snowflake

Python

ETL tools

Job description

What you'll do

Eaton is looking for a motivated Apprentice to join its Master Data Management (MDM) team. This role offers hands‑on experience with modern data platforms, including Snowflake, Data Architecture, Medallion Architecture, and emerging Generative AI (GenAI) capabilities.

You will work closely with senior data engineers and architects to support data engineering, data quality, and data governance initiatives while building foundational skills in enterprise data management.

Key Responsibilities

• Support development and maintenance of MDM solutions on modern cloud platforms (Snowflake preferred)
• Assist in implementing Medallion Architecture (Bronze, Silver, Gold layers) for structured data processing
• Write and optimize SQL queries for data transformation, validation, and analysis
• Take part in data modeling and data architecture discussions
• Support data quality, cleansing, and standardization initiatives
• Assist in building data pipelines, Streamlit apps, and workflows
• Explore and prototype GenAI-driven use cases in data management (e.g., intelligent matching, enrichment, automation)
• Collaborate with cross‑functional teams, including data stewards, business stakeholders, and engineering teams
• Document technical designs, transformations, and best practices

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related field

Skills

• Basic understanding of SQL (joins, aggregations, transformations)
• Familiarity with Data Warehousing concepts
• Knowledge of Snowflake or any cloud data platform (preferred)
• Understanding of Data Architecture fundamentals
• Awareness of Medallion Architecture (Bronze‑Silver‑Gold layers)
• Basic knowledge or interest in Generative AI (GenAI) concepts and applications
• Exposure to ETL/ELT processes is a plus
• Certification or coursework in Snowflake, Data Engineering, or AI/ML
• Hands‑on academic or project experience in data‑related domains

Soft Skills and Behavioral Competencies

• Strong analytical and problem‑solving mindset
• Good communication skills (ability to explain technical concepts clearly)
• Willingness to learn and adapt in a fast‑paced environment
• Attention to detail and data accuracy
• Ability to work collaboratively in a team environment
• Proactive attitude with a self‑starter mindset
• Openness to feedback and continuous improvement
• Strong time management and prioritization skills

Useful extras include exposure to tools like Python or data integration tools, an understanding of data governance and data quality frameworks, and basic knowledge of APIs and data services.