Data Engineer – Snowflake

• Build and support non-interactive (batch, distributed) and real-time, highly available data pipelines
• Build fault-tolerant, self-healing, adaptive, and highly accurate data computational pipelines
• Provide consultation and lead implementation of complex programs
• Develop and maintain documentation for assigned systems and projects
• Tune queries running over billions of rows in a distributed query engine
• Perform root cause analysis to identify permanent resolutions to software or business process issues

• Strong background in data engineering, specifically within Databricks and Azure
• Proficiency in SQL and Python
• Comfortable with Spark, data management, cloud services, and automation tools
• Agentic AI and Snowflake
• SQL Server (T-SQL, query-heavy, not ORM)
• PostgreSQL (read-only, for the Cargotel replica)
• Python and FastAPI
• scikit-learn (percentiles, outlier detection)
• Understanding of acceptance/likelihood models (carrier-accept-probability logic)
• Kafka (consuming, not building)
• Ability to read C# well enough to extract logic, not write it
• AWS basics: S3, RDS, Secrets Manager, CloudWatch
• Terraform (read fluency)
• Proven industry experience executing data engineering, analytics, and/or data science projects, or a Bachelor's/Master's degree in quantitative studies including Engineering, Mathematics, Statistics, Computer Science, or computation-intensive Sciences and Humanities

• Flexibility, with remote and hybrid work options (country-dependent)
• Career advancement, with international mobility and professional development programs
• Learning and development, with access to cutting-edge tools, training and industry experts
• Competitive compensation package