Analytics Engineer

emagine Polska; Lisboa; Presencial; EUR 60 000 - 90 000; Tempo integral

Resumo da oferta

emagine Polska is seeking a data engineering professional to design scalable data models and semantic layers, and to build and monitor ELT pipelines across cloud platforms.

You will ensure data quality, lineage, and governance while supporting BI, Analytics, and ML teams with reliable data products. Collaboration with cross-functional teams is essential for delivering business value.

Qualificações

• Experience with dimensional modeling and data vault/medallion architecture.
• Strong SQL skills with optimization and tuning.
• Proficiency in Python and Spark SQL for data processing.

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

Data governance

Data lineage

Ferramentas

Azure Data Factory

Airflow

Databricks

Microsoft Fabric

Snowflake

Synapse

BigQuery

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.