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Job DescriptionStrategic Mandate
As a Senior Data and AI Engineer II, your mandate is to bridge the gap between architectural design and hands-on execution. Reporting into the Lead Data and AI Engineer, you will be a key contributor to the AI Braintrust, focusing on the technical industrialization of our Databricks environment. This role is built for a "Strategic Executor"—someone who understands the functional "how" of scaling AI pipelines while maintaining a sharp focus on the "why" behind business requirements from Finance, HR, and Product stakeholders.
Core Goals & Responsibilities
Databricks Engineering: Execute the end-to-end build of data solutions within the Databricks ecosystem, ensuring all pipelines are optimized for performance and cost-efficiency (FinOps).
Unity Catalog Implementation: Assist in the definition and rigorous maintenance of the Unity Catalog to ensure data governance, residency, and security protocols are met across all workflows.
Modern Tooling & Frameworks: Develop and maintain transformation layers using dbt, and leverage Python and Heavy SQL to build resilient data structures.
AI Orchestration: Implement GenAI patterns using LangChain and open-source data formats to transition experimental models into production-ready features.
Collaborative Delivery: Work in lockstep with CloudOps and DevOps to ensure seamless CI/CD integration and 99.99% system reliability.
Stakeholder Engagement: Partner with owners in Finance and HR to ensure data outputs are accurate, actionable, and aligned with departmental goals.
Expertise & Technology Stack
Experience: 5+ years of progressive experience in data engineering, with a focus on cloud-native architectures.
Technical Proficiency: * Advanced Python and SQL skills.
Hands-on experience with dbt for data modeling.
Exposure to AI frameworks such as LangChain.
Cloud Infrastructure: Familiarity with AWS environments and automated deployment patterns.
Problem Solving: A pragmatic approach to engineering; you focus on building sustainable solutions rather than "over-engineering" for the sake of complexity.
- Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
- Certifications: * Preferred: Databricks Certified Data Engineer Associate/Professional.
- Bonus: AWS Certified AI/ML Specialty.
- Communication Style: Direct and scannable. You prioritize BLUF (Bottom Line Up Front) communication when reporting status or risks to technical leads and business partners.
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