Senior Analytics Engineer (dbt/SQL/AI) - Remote Portugal

ABOUT THE OPPORTUNITY

Join a world-class technology consultancy as an Analytics Engineer, playing a key role in shaping how data is modeled, understood, and used across the business. You'll turn raw data into meaningful, well-structured insights that drive better decisions. This role offers you the opportunity to build robust data models, create well-governed data layers, and explore embedding AI across analytics workflows to automate repetitive work and enable teams to focus on higher-value problem-solving.

PROJECT & CONTEXT

You'll design and maintain clean, well-structured data models that support analytics, reporting, and self-serve use cases on an established data platform. The role focuses on building scalable data models that make data intuitive and accessible for the business while balancing performance, usability, and long-term maintainability. You'll write efficient SQL to transform raw data into trusted, business-ready datasets with reusability front of mind. Working closely with stakeholders, you'll understand key business questions and ensure data is modeled to answer them effectively. You'll explore embedding AI within analytics workflows—automating repetitive tasks and designing data structures that enable LLMs to effectively answer natural language questions through proper structure, context, and semantics. Contributing to data quality, testing, and documentation, you'll apply best practices while making pragmatic trade-offs for real-world data systems.

WHAT WE'RE LOOKING FOR (Required)

• SQL-first mindset: Strong, instinctive use of SQL to solve complex data problems and build transformations
• Data transformation frameworks: Proven experience building data models using dbt, SQLMesh, or similar transformation frameworks
• Data architecture understanding: Solid grasp of data architecture and how different layers of the data stack fit together
• Data modeling expertise: Strong skills with appreciation for trade-offs between performance, simplicity, and flexibility
• Cloud data warehouse experience: Hands-on work with platforms like Snowflake, BigQuery, or Redshift on large-scale datasets
• Business-driven approach: Genuine interest in how data drives business outcomes, not just technical implementation
• Stakeholder collaboration: Ability to work closely with business users to understand questions and model data effectively
• Best practices application: Experience applying data modeling best practices while making pragmatic real-world trade-offs
• Data quality focus: Contribution to improving testing, documentation, and data quality across analytics layers
• Collaborative mindset: Friendly, collaborative approach with willingness to share ideas and learn from others
• Language requirement: Fluent English (mandatory)

NICE TO HAVE (Preferred)

• Experience with AI-powered analytics tools and LLM integration for data querying
• Knowledge of semantic layers and metadata management for enabling natural language data access
• Familiarity with data observability and monitoring tools
• Background in automating analytics workflows and data pipeline orchestration
• Experience with data governance frameworks and data cataloging
• Understanding of dimensional modeling methodologies (Kimball, Inmon, Data Vault)
• Exposure to DataOps practices and version control for analytics code