Scientific Data Management

Position Overview

Do you enjoy collaborating with a diverse group of people to solve complex challenges? Does contributing to breakthrough discoveries in science and working with unique experimental instrumentation in a world-leading scientific research environment excite you? The Experimental Data Systems (EDS) division within the Linac Coherent Light Source (LCLS) Directorate at SLAC is seeking a Big Data Architect to work on the development of data management tools that enable LCLS scientific capabilities.

LCLS is the world¿s premier X-ray free-electron laser (XFEL) with a suite of X-ray instruments capable of generating large, high-velocity, high-variety datasets used to elucidate atomic structures and dynamics at the femtosecond timescale. The evolution of science and experimental techniques on these instruments, along with upgrades in the X-ray FEL source and optical lasers (LCLS-II and LCLS-II-HE), benefits from real-time feedback, access to significant computing power, innovative analysis methods such as those employing AI/ML, and the ability to automate experiments from execution to analysis.

This position will focus on the development, integration, and management of systems to transport, store, search, retrieve, analyze, and visualize petascale scientific datasets. The successful applicant will participate in the effort to develop systems that enable the seamless transfer of data to Department of Energy Leadership Class Facilities for real-time analysis. A significant aspect of the role will be to support, maintain, and optimize existing EDS software and hardware platforms at the SLAC Shared Data Facility (S3DF) to support LCLS operations.

As a Big Data Architect in the LCLS Data Management Department, you will work within an interdisciplinary team of software developers, scientists, and engineers and oversee scientific data management systems, including data curation, timely data transfer, and archival integrity for LCLS. Responsibilities include overseeing data transfer, replication, and backup processes, building and testing automation tools, and participating in the development of next-generation scientific instruments that connect to remote computing resources to execute time-intensive and data-intensive workflows. In addition to maintaining and automating data management activities at LCLS, the successful candidate will also work on data management solutions with scientific and operations support staff to develop future scientific instrumentation capabilities.

Your Specific Responsibilities Include:

• Work with the LCLS Data Systems team, beamline scientists, SLAC Shared Scientific Data Facility, and SLAC IT to ensure the complete and timely delivery of data from LCLS instruments to the S3DF and remote DOE computing facilities.
• Oversee the LCLS data repositories, ensure their integrity, enforce data retention and access policies, and manage data movement for purposes of analysis or archival.
• Interface with the LCLS Data Systems team and Department of Energy Advanced Scientific Computing Facility partners to understand future data requirements and design Big Data systems that are scalable, optimized, and fault-tolerant, specifically in the context of multi-facility data processing.
• Develop, test, implement, and maintain database management applications.
• Contribute to the development of guidelines, standards, and processes to ensure LCLS data quality, integrity, and security of systems and data.
• Partner with LCLS scientist data owners and Data Systems team members to understand the types of data collected at LCLS and suggest new tools or methods to improve data ingestion, storage, and access to LCLS datasets to ensure data are FAIR and AI-ready.
• Document system builds and application configurations; maintain and update documentation as needed.
• Serve as a technical resource for applications.
• Follow team software development methodology.
• Other duties may also be assigned.

To Be Successful In This Position You Will Bring:

• Bachelor's degree and five years of relevant experience, or a combination of education and relevant experience.
• Demonstrated experience in designing, developing, testing, and deploying applications.
• Strong understanding of data design, architecture, relational databases, and data modeling.
• Knowledge of key data structures, algorithms, and techniques pertinent to systems that support high-volume, high-velocity, or high-variety datasets, including data mining, machine learning, NLP, and data retrieval.
• Experience in parallel and distributed data processing techniques and platforms (MPI, MapReduce, Batch).
• Experience in scripting languages and debugging.
• Ability to analyze systems and data pipelines and propose solutions that leverage emerging technologies.
• Experience deploying reliable data systems and data quality management.
• Ability to research, evaluate, architect, and deploy new tools, frameworks, and patterns to build scalable Big Data platforms.
• Thorough understanding of all aspects of the software development life cycle and quality control practices.
• Strong communication skills with both technical and non-technical clients.
• Ability to select, adapt, and effectively use a variety of programming methods.
• Ability to recognize and recommend needed changes in user and/or operations procedures.

Certifications and Licenses

None

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, maintaining an open outlook while adjusting and accommodating changes.
• Communication: Ensures effective information flow to various audiences and creates and delivers clear, appropriate written and spoken messages.
• Relationships: Builds relationships to foster trust, collaboration, and a positive climate to achieve common goals.

Job-Specific Competencies

• Comfortable writing efficient, scalable, and documented code in Python or C/C .
• Experience with libraries and frameworks such as Rucio, Kafka, ZeroMQ, Kubernetes, Jupyter, and Grafana is a plus.

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 his or her job.

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,

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• Classification Title: Big Data Architect 1
• Grade: K, Job Code: 4734
• Employment Duration: Regular Continuing

The expected pay range for this position is $157,945 - $177,385 per annum. SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of what the university reasonably expects to pay for a position. 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.