Senior HPC Data Engineer

About our customer:

Our client is a global company specializing in software development and consulting who combines science and technology with deep industry expertise to solve complex subsurface and surface challenges in the evolving energy sector.
The client headquartered is located in Canada, with offices around the world. The company serves organizations globally, providing cutting-edge software technology and unparalleled customer support.

Key Software Solutions:
Our client offers a range of reservoir simulation software, including:

• IMEX – A black oil simulator for primary, secondary, and tertiary recovery processes.
• GEM – An advanced simulator for compositional, chemical, and unconventional reservoir modeling.
• STARS – The industry standard for thermal and advanced recovery processes.
• CMOST – An intelligent optimization and analysis tool that integrates statistical analysis, machine learning, and unbiased data interpretation to determine optimal reservoir solutions.

The company invests in research and development, continuously improving its products and delivering state-of-the-art solutions for energy modeling and optimization.

About the Role:

We are looking for an experienced Data Service Module Engineer to develop and deploy the data service module for the HPC modeling project. This role focuses on implementing high-performance data storage and retrieval systems using HDF5 or similar, with parallel and concurrent I/O capabilities. The ideal candidate will have expertise in designing scalable data services optimized for HPC or distributed workflows, ensuring low latency and high throughput.

Key Responsibilities:

• Design and implement the data service module using HDF5 for efficient data storage and retrieval.
• Develop parallel and concurrent I/O mechanisms to optimize performance for large-scale datasets.
• Ensure the module is tightly integrated with HPC and visualization workflows.
• Optimize I/O operations for CPU/GPU-based workflows to minimize bottlenecks.
• Implement caching, compression, and other strategies to enhance performance.
• Design data structures and schemas suitable for storing 3D grid data and other simulation outputs.
• Ensure data integrity and consistency during concurrent read/write operations.
• Develop and execute test cases to validate module performance and reliability under various load conditions.
• Conduct benchmarking to ensure scalability across different hardware configurations.
• Document the architecture, APIs, and usage guidelines for the data service module.
• Provide technical support to the development and visualization teams for data integration.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related fields.
• 2+ years of experience in developing and deploying data services for HPC or similar systems.
• Proven expertise in Big Data
• Proven expertise with HDF5 or similar, in parallel I/O operations. Equivalent experience in distributed systems is also applicable.
• Programming: Strong proficiency in Python. An additional experience with C++ and/or Rust is a nice to have and it will be considered a plus
• HDF5 Expertise: In-depth knowledge of HDF5 APIs and advanced features like parallel HDF5.
• Parallel I/O: Experience with MPI I/O, POSIX I/O, or similar frameworks for concurrent/parallel data access.
• Performance Optimization: Skills in profiling and optimizing I/O operations for large datasets.
• Proficiency in SQL and experience with any RDMS
• Might be a plus: knowledge of at least one orchestration and scheduling tool, for example, Airflow, Prefect, Dagster, etc.
• Strong problem-solving skills and ability to work in a multidisciplinary team.
• Excellent communication skills for cross-team collaboration and documentation.

Preferred Qualifications:

• Familiarity with data formats used in scientific computing, 3D visualization, and simulation workflows.