Analytics Engineer
⚲ Lisbon
Do uzgodnienia
Wymagania
- Documentation
- Business Intelligence (BI)
- Machine Learning (ML)
- Governance
- SQL
- Python
- Spark
- Cloud
- Microsoft Azure
- CI/CD
Opis stanowiska
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.
• 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.
🔍 Dekoder Ogłoszenia
🔴
Collaborate with cross-functional teams to deliver business value.
Może oznaczać, że będziesz musiał tłumaczyć skomplikowane zagadnienia techniczne na język biznesu i często brać udział w spotkaniach z nietechnicznymi działami.
🔴
Ensure documentation of business rules, data lineage, and transformations.
Może oznaczać, że dokumentacja jest zaniedbana i będziesz musiał ją tworzyć od zera lub znacząco poprawiać.
🔴
Support BI, Analytics, Data Science, and ML teams with reliable data products.
Może oznaczać, że będziesz głównie "naprawiał" istniejące problemy z danymi dla innych zespołów, zamiast budować nowe rozwiązania.
🟡
Experience with CI/CD, version control, and DataOps practices.
Wymaganie to może być bardzo ogólne i niekoniecznie oznaczać wdrożone i dojrzałe procesy DataOps, a jedynie podstawową znajomość narzędzi.
🟡
Advanced SQL, including query optimization and performance tuning.
Chociaż brzmi to jak standardowe wymaganie, może sugerować, że obecne zapytania są bardzo nieoptymalne i wymagają gruntownej przebudowy.