Data and AI Engineer II

About the role

As the Data and AI Engineer II, you will serve as a project leader and independent contributor on a fast-growing Data Engineering team focused on analytics-driven mining. Your expertise in data and software engineering will enable the organization to build and deploy data- and AI-driven solutions to production while collaborating with mining operations, subject matter experts, data scientists, and software engineers. You will champion DataOps and agile practices to drive value across projects.

Responsibilities

• Lead technical work within cross-functional, geographically distributed agile teams
• Design, develop, review, and maintain real-time and bulk data pipelines, feature stores, and vector stores
• Ensure adherence to design patterns
• Develop data lineage and data dictionary documentation
• Apply DataOps best practices
• Provide thought leadership in problem solving, challenge paradigms constructively, solicit input, and participate in R&D initiatives
• Utilize Snowflake, Azure, and DevOps/DataOps/MLOps practices to deliver enterprise-quality Python and SQL solutions and identify optimization opportunities
• Independently pursue training and research emerging technologies for departmental application
• Perform other duties as requested

Qualifications

• Bachelor's degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline and five (5) years of relevant work experience OR
• Master's degree in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline and three (3) years of relevant work experience OR
• Ph.D. in engineering, computer science, analytical field (Statistics, Mathematics, etc.) or related discipline and one (1) year of relevant work experience

Required Skills

• Knowledgeable Practitioner of SQL development with experience designing high quality, production SQL codebases
• Knowledgeable Practitioner of Python development with experience designing high quality, production Python codebases
• Knowledgeable Practitioner in data engineering, software engineering, and ML systems architecture
• Hands-on experience building production data workloads in Snowflake, including warehouse and schema design, with awareness of the performance and cost implications of design choices
• Knowledgeable Practitioner of data modeling
• Experience applying software development best practices in data engineering projects using GitHub and GitHub Actions, including Version Control, P.R. Based Development, Schema Change Control, CI/CD, Deployment Automation, Test Driven Development/Test Automation, Shift left on Security, Loosely Coupled Architectures, Monitoring, Proactive Notifications using Python and SQL
• Experience delivering machine learning or generative AI solutions to production, including model or LLM integration, evaluation, and monitoring
• Data science experience wrangling data, model selection, model training, model validation, Operational Readiness Evaluator and Model Development and Assessment Framework, and deployment at scale

Preferred Qualifications

• Working knowledge of Azure Stream Architectures, dbt on Snowflake, Schema Change tools, Data Dictionary tools, Azure Machine Learning Environment, GIS Data
• Working knowledge of generative AI tooling, LLM APIs, prompt design, vector databases, and RAG patterns, and of MLOps practices for model deployment and monitoring
• Working knowledge of Software Engineering and Object Orient Programming Principles
• Working knowledge of Snowflake-native capabilities such as Snowpark, Streams and Tasks, Dynamic Tables, and Cortex AI
• Working knowledge of Distributed Parallel Processing Environments such as Spark
• Working knowledge of problem solving/root cause analysis on Production workloads
• Working knowledge of Agile, Scrum, and Kanban
• Working knowledge of workflow orchestration using tools such as Airflow, Prefect, Dagster, or similar tooling
• Working knowledge of GitHub and GitHub Actions for source control and CI/CD, or comparable tooling
• Experience with containerization tools such as Docker
• Strong verbal and written communication skills in English language

Pay

The estimated annual pay range for this role is currently $112,000-$160,000. This range reflects base salary only and does not include bonus payments, benefits or retirement contributions. Actual base pay is determined by experience, qualifications, skills and other job-related factors. This role is eligible for additional incentive compensation considerations based on company and individual performance. Additionally, this position is currently eligible for annual long-term incentive consideration. Long-term incentives are contingent upon authorized approval under the terms and conditions of the Company's plan and award agreements.

Benefits

• Affordable medical, dental and vision benefits
• Company-paid life and disability insurance
• 401(k) plan with employer contribution/match
• Paid time off, paid sick time, holiday pay, parental leave
• Tuition assistance
• Employee Assistance Program
• Discounted insurance plans for pet, auto, home and vehicle
• Internal progression opportunities

Schedule

Employees may be required to work a non-standard schedule, which may include shift work (other than day shift) at a 24/7, 365-day operation.