Data Engineer

📋 Description

• Design, build, and maintain scalable data pipelines and products for internal and external use.
• Build and optimize batch and near real-time data ingestion, transformation, and delivery.
• Integrate data from internal and external sources to support analytics.
• Collaborate with data teams and stakeholders to deliver scalable data solutions and dashboards.
• Design and implement data models that support reporting, analytics, and operational use cases.
• Ensure data quality, reliability, and performance via monitoring, validation, and testing.

🎯 Requirements

• 2–4 years in Data Engineering, Data Warehousing, or related roles.
• Strong Python and SQL for building scalable data pipelines.
• Experience with Apache Spark, Parquet, and Azure Databricks.
• Strong SQL expertise: performance tuning, indexing, partitioning, and optimization.
• Solid understanding of ETL/ELT, data warehousing principles, and best practices.
• Experience with BI tools (Sisense) and CI/CD pipelines (GitLab/Jenkins).

🎁 Benefits

• Opportunity to evolve and enhance a modern data platform.
• AI-assisted development tools to improve productivity and quality.
• Collaborative, cross-functional team environment.
• Flexible remote work with global teammates.