Analytics Engineer

emagine; Lisboa; Presencial; EUR 55 000 - 75 000; Tempo integral

Resumo da oferta

emagine Lisboa seeks an experienced data engineer to design scalable data models, build robust ELT pipelines, and ensure data quality across analytics teams.

You will collaborate with BI, data science, and business teams, apply modern DataOps practices, and work with Snowflake, Databricks, and Azure tools to deliver reliable data products.

Qualificações

• Experience with dimensional modeling, Medallion architecture, and semantic layer design.
• Experience building ELT pipelines using tools such as Azure Data Factory, Airflow, Microsoft Fabric, or Databricks.

Responsabilidades

• Design and maintain scalable data models and semantic layers.
• Build, optimize, and monitor ELT pipelines and data quality processes.
• Ensure documentation of business rules, data lineage, and transformations.
• Monitor data performance, availability, and SLAs.
• Support BI, Analytics, Data Science, and ML teams with reliable data products.
• Collaborate with cross-functional teams to deliver business value.

Conhecimentos

Dimensional modeling

Medallion architecture

Semantic layer design

Advanced SQL

Python

PySpark

Spark SQL

CI/CD

DataOps

Data quality

Observability

Governance

Data lineage

Power BI semantic modeling

DAX optimization

Ferramentas

Azure Data Factory

Airflow

Microsoft Fabric

Databricks

Snowflake

Synapse

BigQuery

Redshift

Delta Lake

ADLS

Power BI

Descrição da oferta de emprego

Responsibilities

• Design and maintain scalable data models and semantic layers.
• Build, optimize, and monitor ELT pipelines and data quality processes.
• Ensure documentation of business rules, data lineage, and transformations.
• Monitor data performance, availability, and SLAs.
• Support BI, Analytics, Data Science, and ML teams with reliable data products.
• Collaborate with cross-functional teams to deliver business value.

Required Qualifications

• Strong knowledge of dimensional modeling, Medallion architecture, and semantic layer design.
• Experience building ELT pipelines using tools such as Azure Data Factory, Airflow, Microsoft Fabric, or Databricks.
• Advanced SQL, including query optimization and performance tuning.
• Proficiency in Python, PySpark, and Spark SQL.
• Experience with CI/CD, version control, and DataOps practices.
• Knowledge of data quality, observability, governance, and lineage.
• Experience with Power BI semantic modeling and DAX optimization.
• Hands-on experience with cloud data platforms such as Snowflake, Synapse, BigQuery, Redshift, Delta Lake, or ADLS.