Analytics Engineers| Data Modeling and Architecture

• Educational Background: A degree in Data Science, Computer Science, Analytics, Machine Learning, or a related domain.
• Language Skills: Proficiency in English at a minimum B2 level or higher.

• Model and transform data into consistent analytical structures.
• Build and optimize ELT pipelines and quality tests.
• Ensure clear documentation (business rules, lineage, transformation logic).
• Monitor datasets, quality, SLAs, and performance.
• Support DS/BI/ML with reliable data and semantic layers.
• Collaborate closely with DE/DS/MLE/PO for integrated and value-driven deliveries.

• Advanced Data Modeling and Architecture: Expertise in star schema, dimensional modeling, medallion architecture, schema evolution management, and semantic layer design.
• Large‑Scale Semantic Layer & Data Model Optimization: Building and optimizing large-scale models, ensuring performance, consistency, and governance.
• Pipeline Orchestration and Automation: Experience with ETL/ELT tools like Azure Data Factory, Apache Airflow, Microsoft Fabric, Databricks Workflows.
• SQL Expertise & Performance Engineering: Proficiency in query tuning, partitioning, clustering, and handling large volumes of data with scalable SQL.
• Advanced Transformations with Python/Spark: Expertise in using PySpark, Spark SQL, and structured Python for advanced data transformations.
• CI/CD and Versioning for Data Pipelines: Experience with implementing CI/CD pipelines, version control, and DevOps best practices for data.
• Data Quality Frameworks & Observability: Rule definition, automated data validation, end-to-end monitoring, and observability.
• Data Governance, Cataloging, and Lineage: Practical use of tools like Microsoft Purview or Unity Catalog for governance, cataloging, and lineage tracing.
• BI Modeling and Performance: Advanced semantic modeling in Power BI, DAX optimization, and efficient analytical model design.
• Cloud Data Warehousing and Technical Architecture: Hands-on experience with platforms like BigQuery, Snowflake, Synapse, Delta Lake, ADLS, and Redshift; understanding system interdependencies.

• Ability to clearly align and bridge the needs of business, Business Intelligence, Data Science, and Data Engineering teams, transforming requests into actionable technical requirements.
• Supports the growth of junior profiles through guidance and functional reviews while promoting collective improvement in the team's output quality.
• Demonstrates accountability for delivering high-quality, consistent, and stable models and analyses while sustaining team trust and reliability.
• Tackles ambiguous issues with a structured approach, identifies root causes, and proposes scalable and effective solutions to mitigate them.
• Easily adapts to shifting priorities, efficiently generates workload plans, and proactively communicates risks to maintain smooth operations.

Mind-blowing workplace culture. You will be integrated in a professional, dynamic and collaborative team.

100% Remote opportunities

We want you to have the flexibility to work where you feel most comfortable and productive.

International Career

• You can expect professional growth and to be connect with the world.
• We are represented in Portugal, Belgium, Luxembourg, and Denmark.
• And with projects in many other countries: Netherlands, Luxembourg, Singapore and in the United States of America (and a lot more is coming…)

If you wish to work with us and you are outside European Union (good news…) we are a Tech Visa Company, We will help!

As a plus, we provide Health and Life Insurance.