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WHO YOU’LL WORK WITH
This role sits at the intersection of Data Platforms (Snowflake, Databricks, Teradata, Trino) and AI-driven innovation helping to drive cutting-edge advancements in both analytics and intelligent automation.
Key Skills & Traits:
5-7 years of experience in designing, building, and optimizing data platforms at scale.
Deep technical expertise in Databricks, Snowflake, Teradata, Trino, and cloud-native data architectures.
Strong programming skills in Python, SQL, and automation frameworks.
Knowledge in AI/ML, GenAI (LLMs, OpenAI, Azure AI), and AI-powered automation.
Solid understanding of data governance, security, and performance optimization.
Passion for leveraging AI to enhance automation, efficiency, and analytics
Proficiency in Python, SQL, and cloud services (AWS, GCP, Kubernetes, Terraform, Docker, CI/CD pipelines).
Experience in building high-performance, scalable, and secure data platforms, ensuring optimal cost, reliability, and governance.
Hands-on experience in data modelling, ELT/ETL pipelines, data lake architecture, and performance optimization.
Strong collaboration, problem-solving, and leadership skills, with the ability to drive initiatives across multiple teams.
WHAT YOU’LL WORK ON
Core Data Platform Responsibilities:
Architect, build, and optimize Snowflake, Databricks, and Teradata platforms to ensure high performance, scalability, and cost-efficiency.
Design and implement advanced data modelling, warehousing, and analytics solutions.
Develop and manage ETL/ELT pipelines, leveraging modern data frameworks and cloud technologies.
Lead efforts in data governance, security, access control, and compliance standards.
Implement observability, performance tuning, and automated monitoring for data platforms.
AI-Driven Enhancements & Automation:
Integrate AI-powered automation into data pipelines, enabling self-healing, anomaly detection, and predictive optimizations.
Build GenAI-powered chatbots and AI agents to improve self-service analytics and platform intelligence.
Enhance data intelligence capabilities using LLMs, RAG (Retrieval-Augmented Generation), and AI-powered search.
Drive AI-driven cost optimization, ensuring efficient resource utilization across cloud platforms.
Evangelize AI adoption in data engineering, helping Nike teams unlock new automation opportunities.
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