IT - Advanced Analytics and Data Solutions Management

Who We Are

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips - the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world - like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

What We Offer

Location:
Bangalore,IND

You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.

At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.

Key Responsibilities

• Design, develop, and maintain scalable data engineering solutions on Azure Databricks, leveraging Delta Lake, Spark, Unity Catalog, and Azure data services to support enterprise analytics and business intelligence requirements.
• Lead end-to-end delivery of enterprise data initiatives, including SAP S/4HANA transformation, SAP BDC integration, business process modernization, and enterprise data platform programs.
• Partner with business, product owners, process owners, and enterprise architects to define data and analytics roadmaps aligned with organizational objectives.
• Collaborate with business stakeholders, solution architects, and cross-functional GIS teams to translate business requirements into efficient, secure, and maintainable data pipelines and data products.
• Develop and optimize batch and real-time data ingestion frameworks, ETL/ELT pipelines, data transformations, and orchestration workflows using Databricks, SQL, Python, and Azure services.
• Ensure data quality, reliability, performance, security, and governance through implementation of monitoring, observability, testing, metadata management, and access control standards.
• Support production operations, incident resolution, root-cause analysis (RCA), and continuous improvement initiatives while adhering to GIS standards, change management processes, and compliance requirements.

• Recognized technical expert in Azure Databricks, Apache Spark, Delta Lake, Unity Catalog, SQL, Python, and Azure Data Platform services.
• Demonstrates strong expertise in data engineering, cloud architecture, data integration, performance optimization, and platform best practices.
• Possesses working knowledge of data governance, metadata management, DevOps, CI/CD, infrastructure automation, and cloud security principles.

• Understands business processes and data domains to design scalable, reusable, and business-aligned data solutions.
• Identifies opportunities to improve data accessibility, operational efficiency, platform performance, and cost optimization through cloud-native architectures and automation.

• Leads complex data engineering initiatives and serves as a technical mentor to junior engineers and project teams.
• Drives technical design reviews, promotes engineering best practices, and contributes to data platform strategy and modernization efforts.
• Collaborates effectively with architects, product owners, and business stakeholders to deliver high-quality solutions.

• Solves complex technical challenges involving data integration, performance tuning, scalability, security, and platform optimization.
• Applies innovative thinking and deep technical expertise to design solutions that address enterprise-scale data processing requirements.

• Influences architecture decisions, engineering standards, and implementation approaches for enterprise data platforms.
• Contributes directly to business outcomes through reliable, scalable, and governed data solutions that enable analytics, reporting, AI, and data-driven decision-making.

• Effectively communicates complex technical concepts to both technical and non-technical audiences.
• Builds strong partnerships across business and technology teams, influencing decisions through technical expertise, collaboration, and trusted advisory relationships.
• Presents solution options, trade-offs, and recommendations to stakeholders and leadership with clarity and confidence.

• Azure Databricks (Advanced)
• Apache Spark & PySpark
• Delta Lake & Unity Catalog
• SQL Server & Advanced SQL
• Python Programming
• Data Modeling & Data Warehousing
• CI/CD (Azure DevOps)
• Git & Source Control
• Data Governance & Metadata Management
• Monitoring, Observability & Cost Optimization
• Performance Tuning and Query Optimization