HR Data Engineer

Position Overview:

SLAC National Accelerator Laboratory's Human Resources Division is seeking a Data Analyst with a strong background in data engineering, pipeline management, and data modeling with related analytical functions. In this role, you will work under general supervision to process a wide range of structured and unstructured HR data while building scalable data pipelines that enable multidimensional data models and advanced analytics.

You will be a key contributor in organizing and integrating data from our new HRIS and HR Data Lake (HRDL) platforms, partnering closely with the Manager of Analytics, Systems, & Training within the HR Directorate. Your work will support the development of reliable, high quality data assets that power reporting, insights, and decision making across HR.

Core responsibilities include making technical decisions within defined parameters related to ETL processes as HR data moves from the HRIS to the HRDL and ultimately into BI platforms. You will also provide informed recommendations to management on broader architectural considerations and collaborate with cross functional partners who manage downstream systems.

This position reports to the Manager of HR Analytics, Systems, & Training and may be performed fully remotely or in a hybrid arrangement, with an expectation of being onsite 2¿3 days per week.

Your specific responsibilities include:

• Perform technical work associated with a wide variety of analytical data and fulfill routine to customized, single and multi-data sources¿ information requests including the following key areas:

Data Engineering & ETL Management:

• Build, maintain, and optimize data pipelines from the HRIS to the HR Data Lake (HRDL). Clean and structure complex datasets using programming languages (SQL, Python, or R) to ensure an accurate "source of truth."
• Accountable for the technical integrity and flow of HR data, ensuring dashboard refresh processes are stable and designed to mitigate risk from potential pipeline failures.

Data Governance & Integrity:

• Research and reconcile discrepancies across systems. Define data standards and perform rigorous validation to ensure high-quality outputs for sensitive HR research.
• Accountable for bolstering the reputation of HR as a data-driven organization worthy of being entrusted with private employee information, and ensures compliant, accurate reporting.

Collaboration & Research:

• Partner with data managers to identify new data sources and improve collection methods. Recommend architectural changes to management and test prototype software.
• Accountable for the continuous improvement of the HR analytics stack, to ensure capabilities are enhanced regularly
• Evaluate and develop new or modifications of usable data from complex data sources. Assess and produce relevant, standard, or custom information (reports, charts, graphs, and tables) from structured data sources by querying data repositories and generating the associated information.
• Devise methods for identifying patterns and trends in available information sources using a variety of qualitative and quantitative techniques. Determine and recommend additional data collection and reporting requirements.
• Design and customize reports based on data in the database. Distribute and disseminate reports to applicable agencies, researchers, management, and other internal end-users.
• Create non-routine databases and generate related information summaries.
• Perform statistical analyses appropriate to complex data and reporting requirements.
• Serve as a resource for non-routine inquiries such as requests for statistics or surveys.
• Lead the implementation of data standards and common data elements for data collection.
• Collaborate with technical staff to standardize and systemize routine reports, dashboards, and metrics.
• May test prototype software and participate in the approval and release process for new software.
• Other duties may also be assigned

To be successful in this position you will bring:

• Bachelor's degree in data science, statistics, information systems, or a related field and three years of relevant experience or combination of education and relevant experience.
• Minimum of 1¿2 years of experience in a data-centric role (Data Analyst, DevOps Engineer, or BI Developer). An equivalent combination of education and experience will be considered.
• Experience handling sensitive or confidential information (e.g. PII, PHI, salary, performance ratings) with extreme discretion.
• Proficiency in SQL is required for data engineering. Familiarity with Python or R for data cleaning and manipulation is also preferred.
• Basic understanding of data architecture concepts, such as ETL (Extract, Transform, Load) processes and how data moves from an HRIS (e.g. Oracle HCM, Workday, or SAP) to a data lake or warehouse (e.g. AWS platforms).
• The ability to use analytical logic to "interrogate" a dataset identifying patterns within complex, unstructured information.
• Strong communication skills, with the ability to translate "data speak" into "people speak" for stakeholders who may not have a technical background.
• In-depth knowledge and experience using and applying analytical software, database management system software, database reporting software, database user interface and query software, and data mining software.
• Demonstrated ability to collect data using a variety of methods, such as data mining and hardcopy or electronic documentation study, to improve or expand databases.
• Intermediate statistical ability.
• Ability to manage multiple activities in a deadline-oriented environment; highly organized, flexible, and rigorous attention to detail.
• Ability to use logic to calculate data; efficiently construct a database or scrutinize the form of a question.
• Ability to work with data of varying levels of quality and validity.
• Demonstrated ability to produce data in a clear and understandable manner meeting user requirements.
• Ability to work effectively with multiple internal and external customers.
• Ability to take a leadership role on projects and with users/clients.

In addition, preferred requirements include:

• Advanced Degree: A Master's degree in a quantitative science field (e.g., Data Science, Statistics, or Computer Science/Engineering).
• Advanced Querying & Scripting: Expertise in SQL. Strong proficiency with Python or R.
• HRIS Ecosystem Knowledge: Hands-on experience with enterprise-grade HRIS platforms such as Oracle HCM, Workday, or SAP SuccessFactors.
• Experience with AWS SageMaker Unified Studio: Proficiency in navigating the Unified Studio environment to manage the end-to-end data lifecycle, including:

Certifications and Licenses:

• Professional Certification: Possession of an AWS Certified Data Engineer/Associate certification strongly preferred.

SLAC Employee Competencies:

• Effective Decisions: Uses job knowledge and solid judgment to make quality decisions in a timely manner.
• Self-Development: Pursues a variety of venues and opportunities to continue learning and developing.
• Dependability: Can be counted on to deliver results with a sense of personal responsibility for expected outcomes.
• Initiative: Pursues work and interactions proactively with optimism, positive energy, and motivation to move things forward.
• Adaptability: Flexes as needed when change occurs, maintains an open outlook while adjusting and accommodating changes.
• Communication: Ensures effective information flow to various audiences and creates and delivers clear, appropriate written, spoken, presented messages.
• Relationships: Builds relationships to foster trust, collaboration, and a positive climate to achieve common goals.

Physical Requirements and Working Conditions:

• Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job. May work extended hours during peak business cycles.
• Given the nature of this position, SLAC is open to hybrid or remote work options

Work standards:

• Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for environment, safety and security; communicates related concerns; uses and promotes safe behaviors based on training and lessons learned. Meets the applicable roles and responsibilities as described in the ESH Manual, Chapter 1¿General Policy and Responsibilities:
• Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide,
• As a national laboratory, SLAC National Accelerator Laboratory is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require employees to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

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• Classification Title: Data Analyst 2
• Grade: I Job code: 4745
• Duration: Regular Continuing

The expected pay range for this position is $108,002 - $128,138 per annum. SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.

At SLAC/Stanford, base pay represents only one aspect of the comprehensive rewards package.