Key skills
AirflowAWSAzureBigQueryCloudETLGoogle Cloud PlatformPythonScalaSQLTableauELTData EngineeringData LakeAnalyticsLookerBIPower BISnowflakeDatabricksGCPGoogle Cloud
About this role
Role Overview
- Technically lead data engineering initiatives within IT Analytics
- Define data architecture (Data Lake, Data Warehouse, pipelines)
- Build and optimize scalable data pipelines (ETL/ELT)
- Ensure data quality, governance, and reliability
- Prepare data for analytical consumption (BI and dashboards)
- Work closely with business areas, translating needs into data solutions
- Mentor other data engineers
Requirements
- Strong experience in data engineering
- Advanced SQL proficiency
- Experience with Python and/or Scala
- Solid experience with data modeling (star schema, snowflake)
- Experience with Data Warehouse and/or Data Lake
- Experience with ETL/ELT and building pipelines
- Cloud: AWS, Azure, or GCP
- Modern platforms: Databricks, Snowflake, BigQuery
- Orchestration: Airflow, Azure Data Factory, or similar
- BI experience (strong plus)
- Knowledge of tools like Power BI, Tableau, or Looker
- Experience creating analysis-ready datasets
- Understanding of metrics, KPIs, and business requirements
Tech Stack
- Airflow
- AWS
- Azure
- BigQuery
- Cloud
- ETL
- Google Cloud Platform
- Python
- Scala
- SQL
- Tableau
Benefits
- Language: Advanced English