Company OverviewKLA is a global leader in diversified electronics for the semiconductor manufacturing ecosystem. Virtually every electronic device in the world is produced using our technologies. No laptop, smartphone, wearable device, voice-controlled gadget, flexible screen, VR device or smart car would have made it into your hands without us. KLA invents systems and solutions for the manufacturing of wafers and reticles, integrated circuits, packaging, printed circuit boards and flat panel displays. The innovative ideas and devices that are advancing humanity all begin with inspiration, research and development. KLA focuses more than average on innovation and we invest 15% of sales back into R&D. Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices. Life here is exciting and our teams thrive on tackling really hard problems. There is never a dull moment with us.
Group/DivisionThe Information Technology (IT) group at KLA is involved in every aspect of the global business. IT's mission is to enable business growth and productivity by connecting people, process, and technology. It focuses not only on enhancing the technology that enables our business to thrive but also on how employees use and are empowered by technology. This integrated approach to customer service, creativity and technological excellence enables employee productivity, business analytics, and process excellence.
Job Description/Preferred Qualifications
The Data Engineer designs, builds, and operates scalable data pipelines and curated data products with a strong focus on SAP data (e.g., S/4HANA or ECC, SAP CRM, and SAP SD/MM). This role is hands-on with PySpark, Python, and SQL, and partners with business and IT stakeholders to deliver trusted datasets for analytics, reporting, and operational use cases.
Key Responsibilities:
Build and maintain robust data pipelines that ingest and harmonize SAP transactional and master data (e.g., Finance, Procurement, Order-to-Cash, Inventory, Manufacturing, Plant Maintenance).
Work with SAP extraction patterns and interfaces such as ODP/CDS views, IDocs, BAPIs/RFCs, and/or SAP BW extractors depending on platform architecture.
Translate SAP process knowledge into analytics-ready data models, including: Master data (e.g., Material, Customer, Vendor, Plant, GL/Cost Center/Profit Center) and Transactional data (e.g., Sales orders, deliveries, invoices, POs, goods movements, production orders)
Develop and optimize PySpark transformations for large-scale datasets; write clean, testable Python utilities for ingestion, validation, and automation.
Author and tune complex SQL transformations, incremental loads, and performance-optimized aggregations.
Contribute to ontology-based modeling by defining Objects, properties, relationships, and (where applicable) actions that align with SAP business processes (e.g., Order, Delivery, Invoice, Material, Supplier).
Implement automated data quality checks (completeness, validity, referential integrity, timeliness) and alerting.
Ensure traceability and auditability through consistent documentation, data lineage, and clear definitions for business-critical metrics.
Participate in code reviews, CI/CD practices for data pipelines, and production support (triage, root cause, prevention).
Collaborate with analysts and BI developers to enable consumption in visualization tools (e.g., Power BI, Tableau, Foundry apps) by publishing well-modeled semantic datasets and curated marts.
Create documentation, onboarding guides, and best practices for SAP data usage and interpretation.
Preferred / Nice to Have:
Palantir Foundry experience (pipeline development, curated datasets, permissions/lineage) and Ontology experience (Objects/relationships).
Familiarity with SAP S/4HANA data models and performance concepts (e.g., CDS views, HANA calculation views).
Experience with BI/visualization tools (Power BI, Tableau, Looker) and building datasets optimized for reporting/semantic layers.
Exposure to data orchestration tools, CI/CD, and data testing frameworks.
Minimum Qualifications
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
Minimum five (5) years of professional experience in data engineering, analytics engineering, or a similar role.
Strong hands-on experience with PySpark, Python, and advanced SQL in production.
Experience engineering pipelines using SAP data sources, including understanding of SAP master/transactional structures and business processes (e.g., OTC, PTP, RTR, manufacturing/inventory).
Working knowledge of data modeling concepts (dimensional modeling, normalization, slowly changing dimensions) and distributed processing fundamentals.
Base Pay Range: $90,400.00 - $153,700.00 Annually
Primary Location: USA-MI-Ann Arbor-KLA
KLA's total rewards package for employees may also include participation in performance incentive programs and eligibility for additional benefits including but not limited to: medical, dental, vision, life, and other voluntary benefits, 401(K) including company matching, employee stock purchase program (ESPP), student debt assistance, tuition reimbursement program, development and career growth opportunities and programs, financial planning benefits, wellness benefits including an employee assistance program (EAP), paid time off and paid company holidays, and family care and bonding leave.
Interns are... For full info follow application link.
KLA-Tencor is an Equal Opportunity Employer. Applicants will be considered for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristics protected by applicable law.
