Analytics Engineer & AI Specialist | Senior | Snowflake

We are a company passionate about people, always prioritizing the quality of our relationships and taking care of every team member. We are looking for someone to join a team that is growing every day, both in size and in professional development.

We encourage and believe in our team, and we value working together. If you are someone with a strong team spirit who seeks continuous growth, BIX is the place for you!

Come join BIX Tecnologia!

Qualifications & Experience

• Experience: 5+ years of dedicated experience in analytics engineering, data engineering, or a related technical role, with proven cross-functional or client-facing exposure.
• AI-Assisted Development: Daily use of AI coding assistants (Cursor, GitHub Copilot, Claude, or equivalent) as a primary development environment is a baseline requirement.
• Advanced SQL & Python: Advanced SQL mastery (window functions, complex CTEs, incremental pipeline patterns without needing documentation) alongside modern, readable Python for automation workflows and data pipelines.
• Snowflake & Cortex Ecosystem: Advanced hands-on experience with Snowflake architecture, Dynamic Tables, and Snowflake Cortex (Cortex Analyst, Cortex Agents, Cortex Search).
• Semantic Modeling & AI Readiness: Proven track record in building semantic layers (e.g., dbt Semantic Layer, Snowflake Cortex definitions) and structuring datasets, metrics, and YAML/Markdown skill files for seamless ingestion by LLMs and natural language search agents.
• Analytics Engineering & dbt: Strong experience building, testing, documenting, and maintaining production-grade dbt projects integrated with CI/CD pipelines and automated QA procedures.
• Fluent English: for clear client-facing and cross-functional communication, with an outcome-driven mindset that codifies patterns into reusable templates and thrives in ambiguous environments.

Key Responsibilities

• Data Modeling & Architecture: Architect performant, flexible, and secure data models in Snowflake using SQL, Python, and dbt to establish single sources of truth across business domains.
• Semantic Layer & AI Agent Readiness: Build and maintain semantic models using Snowflake Cortex Analyst to expose complex schemas to natural language interfaces, ensuring metrics, dimensions, and relationships allow AI agents to reason correctly.
• AI Quality & Gap Resolution: Identify and resolve structural, naming, or coverage gaps in datasets that could cause downstream AI agents or LLMs to produce incorrect results.
• Codification & Template Creation: Document reusable playbooks, data model templates, and semantic view configurations (YAML/Markdown) that enable non-technical stakeholders or engineers to deploy standardized solutions.
• Data Governance & Security: Oversee data QA, automated testing, data security, permissions, lineage, and definitions to ensure data is structured, trusted, and agent-ready.
• Mentorship & Upskilling: Conduct technical workshops to raise the technical bar for the team and translate complex technical architecture into actionable business insights for client stakeholders.