Role OverviewLead the architecture and technical direction of the enterprise data platform, designing scalable, secure, and resilient data ecosystems supporting analytics, operational reporting, and AI/ML workloads.
What You Will Do
Architect modern data pipelines, data warehouses, and machine learning infrastructure, partner with Product, Analytics, and Data Science teams to translate complex business challenges into scalable data and AI solutions.
Why It Might Be a Fit
Serve as the technical authority for enterprise data architecture and long-term platform strategy, mentor senior engineers and influence engineering excellence across multiple teams.
Requirements
- 10+ years of experience in Data Engineering, Analytics Engineering, or Machine Learning Engineering
- Experience as a Principal Engineer, Data Architect, or Technical Lead owning enterprise-scale data platforms
- Expert-level proficiency in Python, advanced SQL, dbt, Apache Airflow, and modern ETL/ELT architectures
- Extensive experience designing and supporting large-scale Snowflake data warehouse environments
- Deep expertise in data modeling, distributed data processing, and cloud-native architecture
- Proven experience enabling production AI/ML platforms and analytics solutions
- Strong understanding of data governance, security, scalability, and engineering best practices
- Demonstrated ability to define technical strategy, establish architectural standards, and influence engineering organizations
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