Own the hands‑on engineering of JD Power's Snowflake data platform, translating architecture and governance into a production‑grade, automated, and observable Snowflake environment that supports analytics, product, and AI/ML workloads across the enterprise.
Locations (2)
United States
Canada
Compensation
This position has a starting salary range of $120,000 – $175,000 USD / $110,000 to $140,000 CAD per year.
Responsibilities
Design, implement, and evolve Snowflake account, warehouse, database, and object architecture
Develop and maintain IaC solutions using Terraform to manage Snowflake environments, security models, and platform configurations
Build and operate CI/CD pipelines for database and platform deployments using tools such as Schemachange, Liquibase, or equivalent technologies
Optimize platform performance through query tuning, clustering strategies, search optimization, materialized views, and workload management
Design and maintain scalable RBAC frameworks
Requirements
Bachelor's degree in Computer Science or related field
The Senior Staff Optical Engineer is a key technical leader responsible for the design, development, and optimization of advanced optical subsystems used in semiconductor failure analysis instrumentation, focusing on high-performance optical systems enabling fault isolation techniques like infrared microscopy, laser stimulation, and photon emission detection.
Responsibilities
Lead the design and optimization of advanced optical subsystems for EFA tools
Infrared (IR) imaging systems for silicon inspection
Laser-based stimulation and probing systems (e.g., LIVA, OBIRCH, TIVA)
Photon emission detection systems (visible and NIR)
Develop optical architectures using simulation tools (Zemax, CodeV, or equivalent)
Senior data engineer responsible for building and maintaining the data foundation for semiconductor industry automation, designing pipelines, and enabling AI-ready data platforms.
Responsibilities
Build pipelines that ingest, persist, cleanse and validate process and telemetry data
Enable data-driven decisions to advance development of high-tech machines for the semiconductor industry
Design a well-governed platform with uniform access, data quality, lineage and observability by default
Make the department AI-ready, so agentic systems can reach our data through clean, well-described interfaces
Work mostly on-premise on Linux, while designing for portability so we stay hosting-agnostic
Requirements
University degree in computer science, software engineering or a related field
The Pricing Analyst will turn pricing, customer, product, transaction, and market data into clear insight. The role is suited to someone with strong quantitative skills who enjoys statistical analysis, modelling, data validation, automation, and communicating findings to commercial stakeholders.
Responsibilities
Analyze pricing, customer, product, and market data to identify trends, opportunities, risks, and performance drivers.
Build and improve pricing models, forecasts, segmentation analysis, sensitivity analysis, and scenarios to support commercial decisions.
Develop repeatable reporting, data validation, and analytical workflows using Excel, Power Query, Python, SQL, and BI tools.
Support monthly and quarterly price forecasting, variance analysis, and commercial performance reviews.
Advanced degree in Mathematics, Statistics, Data Science, Engineering, Economics, Operations Research, or a related quantitative field; or a bachelor’s degree with approximately 2+ years of relevant analytics, pricing, commercial operations, finance analytics, or data science experience.
Work on backend platform software that powers advanced scientific instruments used in semiconductors, life sciences, and materials research. The role drives reliable, scalable VM infrastructure automation and CI/CD execution.
Responsibilities
Development of backend automation services (Python/C#) for process execution, file operations, health checks, and environment management
Digital Personalization Specialist focused on building, running, and scaling personalization experiments and campaigns to drive growth across web, app, and other channels.
Responsibilities
Own and manage the audience playbook across the organization
Maintain the enterprise audience playbook as the single source of truth for segments, eligibility rules, signal sources, and naming/taxonomy
Build, QA, and govern audiences and segments in the CDP and personalization platform
Enforce governance standards that prevent personalization tech debt
Partner with CRM teams to enhance and optimize enterprise audience strategies