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.