Data Engineer
Summary
Builds and maintains scalable ETL/ELT pipelines and data platforms using Python, SQL, PySpark, and Azure services like Databricks and Data Factory.
We are looking for aData Engineer with strong experience designing and developing scalable data solutions in cloud environments. This role will be responsible for building and optimizing data pipelines, enabling reliable data platforms, and collaborating with global technical and business teams.
Responsibilities
- Design, develop, and maintain scalableETL/ELT data pipelines.
- Build and optimize data workflows for large-scale data processing.
- Develop data models for analytics and reporting.
- Ensure data quality, performance, and reliability.
- Collaborate with Data Analysts, Data Scientists, Product Owners, and business stakeholders.
- Implement best practices in Data Engineering, DataOps, CI/CD, and documentation.
Technical Requirements
- 3+ years of experience as a Data Engineer.
- Advanced experience withPython and SQL.
- Strong knowledge ofApache Spark / PySpark.
- Hands-on experience with cloud data platforms, preferablyAzure:
- Azure Databricks
- Azure Data Factory (ADF)
- Azure Data Lake Storage (ADLS)
- Azure Synapse (nice to have)
- Experience with Data Lake, Data Warehouse, and Lakehouse architectures.
- Experience with orchestration tools such asAirflow or similar.
- Experience usingGit, CI/CD practices, and Agile methodologies.
Profile
- Strong problem-solving and analytical skills.
- Ability to work independently and own end-to-end data solutions.
- Experience working with global and cross-functional teams.
- Advanced English level (B2+/C1) required.