Analytics Engineer

powertalent; Portugal; Híbrido; EUR 55 000 - 75 000; Tempo integral

Resumo da oferta

powertalent seeks an Analytics Engineer to lead design, implementation and optimization of advanced analytical solutions. You will mentor team members and align technical decisions with business goals to drive cross-disciplinary decision-making.

You will design scalable data models, build semantic layers, and develop automated ETL/ELT pipelines using modern cloud tools. Expect a strong focus on data quality, governance, and robust BI models in a hybrid work setting.

Qualificações

• Minimum 3+ years in data analytics environments with hands-on contribution to reliable data solutions.
• Experience designing scalable data models (star schema, dimensional modeling) and semantic layers.
• Strong SQL tuning, data pipeline development (ETL/ELT) and data quality monitoring.

Responsabilidades

• Design and implement scalable data models (star schema, dimensional modeling) and maintain controlled schema evolution.
• Build and optimize large-scale semantic layers and analytical data models for performance and governance.
• Develop and maintain automated ETL/ELT pipelines using tools like Azure Data Factory, Databricks Workflows, Airflow, or Microsoft Fabric.
• Optimize data structures and queries with advanced SQL techniques for large datasets.
• Develop transformations using Python, PySpark, and Spark SQL for scalable processing.
• Implement CI/CD, version control, and DevOps practices for data pipelines.
• Define data quality frameworks and observability solutions with automated validation and SLA tracking.
• Apply data governance, cataloging, and lineage using Purview or Unity Catalog.
• Build and optimize Power BI semantic models with advanced DAX optimization.
• Work with cloud data platforms such as Snowflake, BigQuery, Azure Synapse, Delta Lake, ADLS, and Redshift.

Conhecimentos

Data modeling

SQL

Python

PySpark

Spark SQL

Data governance

Mentoring

Problem solving

Communication

Ferramentas

Azure Data Factory

Databricks

Airflow

Microsoft Fabric

Snowflake

BigQuery

Azure Synapse

Delta Lake

ADLS

Power BI

Purview

Unity Catalog

Descrição da oferta de emprego

We are seeking motivated and skilled Analytics Engineer to lead the design, implementation, and optimization of advanced analytical solutions. This exciting opportunity demands strategic thinkers who can align technical decisions with business goals, mentor team members, and drive impactful decision-making across interdisciplinary groups.

Responsibilites

• Design and implement scalable data models (star schema, dimensional modeling, medallion architecture), ensuring consistency, maintainability, and controlled schema evolution
• Build and optimize large-scale semantic layers and analytical data models, focusing on performance, reusability, and governance
• Develop and maintain automated ETL/ELT pipelines, using tools such as Azure Data Factory, Databricks Workflows, Apache Airflow, or Microsoft Fabric
• Optimize data structures and queries using advanced SQL techniques, including query tuning, partitioning, clustering, and performance optimization for large datasets
• Develop complex transformations using Python, PySpark, and Spark SQL, ensuring scalability and efficiency
• Implement CI/CD, version control, and DevOps best practices for data pipelines, ensuring reliable and secure deployments
• Define and implement data quality frameworks and observability solutions, including automated validation, monitoring, and SLA tracking
• Apply data governance, cataloging, and lineage practices using tools such as Microsoft Purview or Unity Catalog
• Build and optimize Power BI semantic models, including advanced DAX optimization and efficient analytical model design
• Work with modern cloud data platforms such as Snowflake, BigQuery, Azure Synapse, Delta Lake, ADLS, and Redshift, understanding cross-system dependencies and architecture

Soft Skills

• Ability to translate business requirements into clear, actionable technical solutions, acting as a bridge between Business, BI, Data Science, and Data Engineering teams
• Experience mentoring and supporting junior and mid-level engineers, promoting best practices and continuous improvement
• Strong ownership mindset, ensuring high-quality, stable, and reliable data solutions
• Structured problem-solving approach with the ability to break down complex and ambiguous challenges into scalable solutions
• Adaptability to changing priorities, with strong workload management and proactive risk communication

Minimum 3+ years in data analytics environments with hands-on contribution to reliable data solutio

Work model: 2 days per week in the office and 3 days at home.