Analytics Engineers| Data Modeling and Architecture at Bridge 351

Lisbon, , Portugal -

Full Time

Start Date

Immediate

Expiry Date

17 Sep, 26

Salary

0.0

Posted On

19 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Yes

Skills

Data Modeling, ELT Pipelines, SQL Performance Tuning, PySpark, Azure Data Factory, Apache Airflow, Microsoft Fabric, Databricks, CI/CD, Data Governance, Power BI, Cloud Data Warehousing

Industry

Software Development

Description

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. Responsibilities: 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. Technical Skills: 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. Soft Skills: 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. What can you expect from us? 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…) Extra Benefits & Perks 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.

Responsibilities

Model and transform data into consistent analytical structures while building and optimizing ELT pipelines. Collaborate with cross-functional teams to provide reliable semantic layers and ensure high data quality and observability.