Databricks Genie Architect

About the Role

As a Databricks Genie Architect, you will be the driving force behind building next-generation conversational data interfaces. Your primary focus will be designing, implementing, and scaling intelligent, natural-language data assistants using Genie.

You will bridge the gap between complex enterprise data warehouses and business users, enabling them to query databases using natural language. This role is a hybrid of cutting-edge Generative AI engineering and robust Data Engineering within the Databricks Lakehouse ecosystem.

Key Responsibilities

Databricks Genie & Conversational AI Development (Core Focus)

• Genie Space Architecture: Design, configure, and maintain high-performing Databricks Genie Spaces tailored to complex business domains.
• Semantic Layer & Curation: Curate semantic metadata, SQL queries, and golden instructions that guide Genie to ensure highly accurate, deterministic SQL generation.
• Testing & Fine-Tuning: Proactively test, benchmark, and fine-tune Genie responses to handle complex business logic, edge cases, and multi-turn conversations.
• Integration & Feedback: Connect Databricks Genie endpoints to custom web interfaces and external UIs, and implement feedback loops to continuously improve accuracy.

GenAI & Data Engineering Support

• Data Pipelines & Spark: Build and optimize data pipelines using Python, SQL, and PySpark to ensure data in Delta Lake is structured and optimized for Genie's consumption.
• GenAI Orchestration: Utilize LLMs on Databricks for metadata enrichment, automated data labeling, and semantic optimization.

Collaboration & Implementation

• Business Translation: Translate business users' questions into data-platform structures and schemas that Genie can answer effectively.

Technical Requirements

Must Have

• 4+ years of hands-on experience with the Databricks ecosystem, with specific focus on Databricks Genie (or equivalent Text-to-SQL/semantic-layer work), Unity Catalog, and Databricks SQL/Workflows.
• Expert-level SQL skills, including writing complex, performant queries, and experience structuring data through star schemas, gold tables, and views to be Genie-ready.
• Strong experience writing clean, production-grade Python code.
• Strong understanding of Text-to-SQL paradigms, prompt engineering, semantic routing, and RAG architectures.
• Proficiency in Apache Spark (PySpark) for data transformation and orchestration.
• Experience working with REST APIs to integrate GenAI endpoints into external applications.

Nice to Have

• MLflow and Model Serving experience, including managing model lifecycles and deploying endpoints using the Databricks AI suite.

Soft Skills

• Analytical and precise, with strong attention to detail when auditing Genie's generated SQL for business accuracy.
• Ability to communicate effectively with business stakeholders, understand their language, and translate it into semantic data models.
• Enthusiasm for keeping up with rapid Databricks and GenAI product updates.

The Offer

Cooperation Models

• Poland: Employment Contract (UoP) or B2B.
• Romania/Greece: B2B only.
• 100% remote: Work from anywhere in Poland, Romania, or Greece.

Benefits

• Apple MacBook Air M4 15-inch provided to all engineers.
• Referral bonus for bringing top-tier engineers to the team.

Professional Growth

• Coverage for all Databricks technical certifications.
• Support in reaching advanced Databricks expertise tiers, such as the Champion program, tailored to your career track.
• Opportunities to present at global industry conferences and contribute to technical thought leadership.
• Direct collaboration with Databricks MVPs and core product teams.

Recruitment Process

• Introductory Call (20 min): Conversation to discuss your background and expectations.
• Technical Interview (60 min): Deep dive into technical skills with the engineering team.
• Optional Client Interview: Required only in specific cases.
• Decision & Offer: The process is intended to close efficiently with prompt feedback.