Senior Data Engineer

Company Overview

KLA 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/Division

The 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/PreferredQualifications

SAP Data Ingestion & Integration

• Design and implement robust ingestion patterns from SAP source systems (S/4HANA/ECC/BW/HANA) and other cloud source systems into Snowflake using enterprise-approved integration tools.
• Build and maintain incremental loads (CDC), batch pipelines, and near-real-time ingestion where needed.
• Understand SAP functional domains and data structures (e.g., FI/CO, MM, SD, PP) to map business requirements to data models.

Snowflake Data Engineering & Modeling

• Develop and optimize ELT/ETL pipelines leveraging Snowflake capabilities (e.g., Snowpipe, Streams & Tasks, Dynamic Tables where applicable).
• Create and maintain curated dimensional and/or data vault models, conformed dimensions, and reusable fact tables for cross-functional analytics.
• Implement data quality checks, reconciliation controls (source-to-target), and exception handling for SAP extracts.

Performance, Cost, and Reliability Optimization

• Tune queries and pipelines for performance using clustering strategies, caching awareness, pruning, warehouse sizing, and workload separation.
• Monitor and manage Snowflake consumption and performance; recommend cost controls (warehouse scheduling, auto-suspend/auto-resume, resource monitors).

Data Governance & Security

• Apply security best practices: RBAC, masking policies, row access policies, and secure data sharing patterns as needed.
• Partner with governance teams to maintain metadata, lineage, glossary alignment, and compliance standards.

Collaboration & Delivery

• Collaborate with BI developers, analysts, and business stakeholders to translate requirements into scalable datasets.
• Contribute to Agile ceremonies and deliver iterative improvements with high engineering standards.
• Document pipelines, models, SLAs, and operational runbooks; participate in on-call/production support rotations as required.

Required Qualifications

• 5-7 years of experience in data engineering, with hands-on development in Snowflake.
• Strong experience integrating SAP data into analytics platforms or data warehouses.
• Strong SQL skills (advanced joins, window functions, query optimization); experience with performance tuning in cloud warehouses.
• Experience building production-grade pipelines using one or more of:
  • Orchestration: Informatica, ADF, dbt orchestration, or similar
  • Transformation: dbt, stored procedures, Snowflake SQL scripting, or equivalent
• Proficiency in Python (or comparable language) for automation, data processing, and pipeline utilities.
• Understanding of data modeling concepts (dimensional modeling, normalization, data vault basics).
• Experience with CI/CD practices (Git, code reviews, deployment pipelines) and environment management (dev/test/prod).

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.

Minimum Qualifications

Doctorate (Academic) Degree and 0 years related work experience; Master's Level Degree and related work experience of 3 years; Bachelor's Level Degree and related work experience of 5 years

We offer a competitive, family friendly total rewards package. We design our programs to reflect our commitment to an inclusive environment, while ensuring we provide benefits that meet the diverse needs of our employees.

KLA is proud to be an equal opportunity employer

Be aware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as KLA employees. KLA never asks for any financial compensation to be considered for an interview, to become an employee, or for equipment. Further, KLA does not work with any recruiters or third parties who charge such fees either directly or on behalf of KLA. Please ensure that you have searched KLA’s Careers website for legitimate job postings. KLA follows a recruiting process that involves multiple interviews in person or on video conferencing with our hiring managers. If you are concerned that a communication, an interview, an offer of employment, or that an employee is not legitimate, please send an email to [email protected] to confirm the person you are communicating with is an employee. We take your privacy very seriously and confidentially handle your information.