Data and AI Engineer II

Freeport McMoRan•Phoenix, AZ

3d•$112,000 - $160,000•Hybrid

About The Position

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.

Requirements

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
Candidates may be required to pass a medical exam.
Candidates must pass all required training and/or testing.
Freeport-McMoRan promotes a drug/alcohol-free work environment using mandatory pre-employment drug testing and on-going drug and alcohol testing, as allowed by applicable laws.

Nice To Haves

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

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; 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.