Apprentice – IT
Eaton
Key Responsibilities
- As an IT Apprentice inside Eaton’s Master Data Management (MDM) team, you will get hands-on enterprise training in scalable data infrastructure. Your daily learning objectives and operational tasks include:
- Supporting the development, migration, and long-term maintenance of advanced corporate MDM solutions using cloud platforms (preferably Snowflake).
- Assisting data architects in implementing Medallion Architecture data pipelines for structured data processing.
- Writing, cleaning, and optimizing SQL queries to assist with internal data transformation, validation, and analytics.
- Participating in standard data modeling routines and data governance design architecture discussions.
- Supporting critical data quality, deduplication, cleansing, and standardization initiatives to maintain data integrity.
- Assisting internal teams in building robust data pipelines, operational workflows, and lightweight Streamlit applications.
- Exploring and prototyping innovative GenAI-driven use cases to automate data enrichment and intelligent record matching.
- Collaborating with cross-functional data stewards, business analysts, and global engineering teams.
- Documenting complex technical transformation designs, architectural workflows, and development best practices.
Skills & Eligibility
- Bachelor’s degree in Engineering (B.E/B.Tech) or Bachelor of Science (B.Sc) specializing in Computer Science, Information Technology, Data Engineering, or related technical disciplines.
- Strong academic records with hands-on academic, boot camp, or personal project experience in data-related domains.
- Basic understanding of database query systems, specifically SQL (handling joins, aggregations, and data transformations).
- Familiarity with functional Data Warehousing and Data Architecture fundamentals.
- Knowledge or foundational awareness of Snowflake or any mainstream cloud data platform is highly preferred.
- Awareness of the modern Medallion Architecture framework (specifically data classification via Bronze, Silver, and Gold operational layers).
- Basic knowledge or an active, proven interest in Generative AI (GenAI) concepts and emerging automation tools.
- Exposure to core data movement methods like ETL / ELT processes is an added plus.
- Academic certifications or specialized coursework completed in Snowflake, Data Engineering, Python, or AI/ML fields will give your profile an edge.
- Strong analytical mind and logic-driven problem-solving capabilities.
- Good corporate communication skills with an capability to describe engineering patterns cleanly.
- Willingness to learn, change, and pivot successfully in a high-tempo enterprise workspace.
- High attention to detail ensuring complete data accuracy and governance integrity.
- Proactive self-starter attitude with a collaborative mindset to excel within global teams.
- Strong time management skills with an ability to prioritize operational sub-tasks effectively.
- Bachelor’s degree in Engineering (B.E/B.Tech) or Bachelor of Science (B.Sc) specializing in Computer Science, Information Technology, Data Engineering, or related technical disciplines.
- Strong academic records with hands-on academic, boot camp, or personal project experience in data-related domains.
- Basic understanding of database query systems, specifically SQL (handling joins, aggregations, and data transformations).
- Familiarity with functional Data Warehousing and Data Architecture fundamentals.
- Knowledge or foundational awareness of Snowflake or any mainstream cloud data platform is highly preferred.
- Awareness of the modern Medallion Architecture framework (specifically data classification via Bronze, Silver, and Gold operational layers).
- Basic knowledge or an active, proven interest in Generative AI (GenAI) concepts and emerging automation tools.
- Exposure to core data movement methods like ETL / ELT processes is an added plus.
- Academic certifications or specialized coursework completed in Snowflake, Data Engineering, Python, or AI/ML fields will give your profile an edge.
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