Senior Data Engineer (SAP & Palantir)
KLA
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Job Description
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
Swing Shift:2-11 pm
About The Company
KLA
KLA develops industry-leading equipment and services that enable innovation throughout the electronics industry. We provide advanced process control and process-enabling solutions for manufacturing wafers and reticles, integrated circuits, packaging and printed circuit boards. In close collaboration with leading customers across the globe, our expert teams of physicists, engineers, data scientists and problem-solvers design solutions that move the world forward. Visit us at: www.kla.com Statements made on LinkedIn may constitute forward-looking statements under federal securities laws. These forward-looking statements involve risks and uncertainties that could significantly affect the expected results and are based on certain key assumptions. Due to such uncertainties and risks, no assurances can be given that such expectations will prove to have been correct, and readers are cautioned not to place undue reliance on such forward-looking statements, which speak only as of the date indicated. Other risks that KLA faces include those detailed in KLA filings with the Securities and Exchange Commission, including KLA's annual report on Form 10-K and quarterly reports on Form 10-Q. Forward-looking statements made by third parties do not necessarily reflect the opinion of KLA, are outside of KLA’s control and have not been verified or otherwise vetted by KLA.
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