Title:  Data and AI Engineer II

What You Will Do

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.

• 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; and 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.

What You Bring To Freeport

• 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 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
• Strong experience in at least three areas:
• 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