Sr Staff Data Scientist

Job Description Summary

You will be part of the core team at GE Vernova Electrification Software (GEV ESW) Business that is using software to enable de-carbonized future of energy by designing, building and delivering software applications & services for next generation Grid Software that is used by 40% of the world's power utilities today. This position is responsible for building our next generation database system, data access and integration layers to meet the intense data demands of next generation power grid software by developing data fabric and semantic data modeling technologies. You will be responsible for designing and implementing highly complex modules, critical components, or a whole application/product in its entirety that enable AI-Based Application that uses multiple distribution and transmission applications using data fabric. This position is both hands on role and will also need to work on developing the AI strategy for Grid Software business. The position is responsible for driving the design and development efforts related to architecture, scalability, availability, and performance in alignment with the product/application roadmap for highly complex database systems for grid of the future technologies.

Job Description

Grid Software (a division of GE Vernova) is driving the vision of GridOS - a portfolio of software running on a common platform to meet the fast-changing needs of the energy sector and support the energy transition. Grid Software has extensive and well-established software stacks that are progressively being ported to a common microservice architecture, delivering a composable suite of applications. Simultaneously, new applications are being designed and built on the same common platform to provide innovative solutions that enable our customers to accelerate the energy transition.

This role is for a senior data architect who understands the core designs, principles, and technologies of GridOS. Key responsibilities include:

• Be responsible for providing technical leadership and defining, developing, and building our next generation data fabric system with focus on semantic modeling, data catalog development, data access and integration layers software in a fast paced and agile development environment.
• Drive innovation in our database systems and drive next level of performance, correctness, durability, and scalability of our data systems by bringing in AI and next generation modeling technologies.
• Feel passionate about developing high performance distributed systems with focus on key database concepts like concurrency control, consensus algorithms, replication, serializability theory, and view maintenance
• Work on developing next generation AI technologies such as Text Mining, Machine Learning, Deep Learning to improve product capabilities and development processes.
• Provide guidance to developers with either planning and execution and/or design architecture using agile methodologies such as SCRUM.
• Work with Product Line Leaders (PLLs) to understand product requirements & develop a strategy and vision.
• Capture system level requirements by brainstorming with CTO, Sr. Architects, Data Scientists, Businesses & Product Managers
• Be responsible for providing technical leadership and defining, developing, and building our next generation data fabric system with focus on semantic modeling, data catalog development, data access and integration layers software in a fast paced and agile development environment.
• Formalizing Data Models and API Standards: Lead the formalization and standardization of data models and API standards across products to ensure interoperability and efficiency.
• Leveraging CIM Standards: Implement and advocate for the Common Information Model (CIM) standards to ensure consistent data representation and exchange across systems.
• Architecture Reviews and Coordination: Contribute to architecture reviews across the organization as part of Architecture Review Boards (ARB) and the Architecture Decision Record (ADR) process.
• Knowledge Transfer and Collaboration: Work with the Architecture SteerCo and Developer Standard Practices team to establish standard practice around data modeling and API design.
• Documentation: Ensure that data modeling and API standards are accurately documented and maintained in collaboration with documentation teams.
• Backlog Planning and Dependency Management: Work across software teams to prepare backlog planning, identify, and manage cross-team dependencies when it comes to data modeling and API requirements.

• AI Technologies: Be knowledgeable and should have implemented AI and GENAI system and must have hands on experience in implementing and training teams in this area.
• Data Architecture and Modeling: Extensive experience in designing and implementing data architectures and common data models.
• API Standards: Expertise in defining and implementing API standards to ensure seamless integration and data exchange between systems.
• Common Information Model (CIM): In-depth knowledge of CIM standards and their application within the energy sector.
• Data Mesh and Data Fabric: Understanding of data mesh and data fabric principles, enabling software composability and data-centric design trade-offs.
• Microservice Architecture: Understandig of microservice architecture and software development
• Kubernetes: Understanding of Kubernetes, including software development in an orchestrated microservice architecture. This includes Kubernetes API, custom resources, API aggregation, Helm, and manifest standardization.
• CI/CD and DevSecOps: Experience with CI/CD pipelines, DevSecOps practices, and GitOps, especially in secure, air-gapped environments.
• Mobile Software Architecture: Knowledge of mobile software architecture for field crew operations, offline support, and near-realtime operation.

• Energy Industry Technologies: Familiarity with key technologies specific to the energy industry, such as Supervisory Control and Data Acquisition (SCADA), Geospatial network modeling, etc.