Azure Databricks Data Engineer_AMAT

Exp: 5+ Yrs
Location: ITPL, Bangalore
Work Mode: 4days Work from Office
Customer: AMAT
Billrate:22-24 LPA

JD:

Minimum 5+ years in Data Engineering, with at least 4 years of hands-on experience in Databricks and Azure ecosystem this is a must.
" End-to-End Data Pipeline Delivery Proven track record of building and owning ETL/ELT pipelines, data models, and platform components at enterprise scale across complex business domains.
" Expert SQL Skills Advanced proficiency in complex joins, window functions, CTEs, query optimization, and performance tuning across large datasets.
" Strong PySpark & Python Hands-on experience building distributed data processing pipelines, transformations, and automation scripts using PySpark and Python.
" Databricks Expertise Deep working knowledge of Delta Lake, Unity Catalog, Workflows, medallion architecture (bronze-silver-gold), notebook development, and lakehouse best practices.
" Clean Code & Engineering Discipline Writes modular, well-documented, and testable code. Follows coding standards, maintains version control hygiene, and builds reusable components that other developers can extend.
" Problem Solving & Debugging Strong ability to diagnose and resolve complex data pipeline failures, distributed system issues, and production incidents under pressure.
" Performance Tuning Demonstrated expertise in optimizing Spark jobs, SQL queries, and storage layers for cost efficiency, throughput, and reliability.
" Developer Ownership Mindset Takes end-to-end responsibility from development through unit testing, deployment validation, and production support not just writing code and handing off.
" Adaptability Comfortable navigating evolving technology stacks, shifting priorities, and cross-functional collaboration in a dynamic, fast-paced Agile environment.
" Team Player Collaborative engineer who actively contributes to code reviews, architecture discussions, knowledge sharing, and mentoring within a globally distributed team.
Nice to Have:
" AI Exposure Familiarity with AI/ML concepts such as model training pipelines, feature engineering, RAG architectures, or tools like Azure OpenAI and LangChain.
" Experience working with supply chain data domains such as procurement, logistics, inventory, or demand planning is a strong plus. Understanding of SAP or ERP data structures in a supply chain context is an added advantage.
" Full Project Lifecycle & Cross-Team Collaboration Has worked through the complete project lifecycle from requirements gathering to production deployment. Experienced in collaborating with API and UI/UX teams, and understands how data flows end-to-end across upstream sources, backend services, APIs, and front-end applications.