Shape the future of data infrastructure by designing and delivering high-performance data solutions at scale. In this role, you will lead the development of modern data platforms using cloud-native technologies, focusing on reliability, efficiency, and security.
What You'll Do
- Design and implement data architectures that support large-scale integration, transformation, and analytics
- Build and maintain automated ETL/ELT pipelines using Azure Data Factory and Databricks
- Optimize data models and query performance in Snowflake for analytical workloads
- Apply PySpark and Spark SQL for processing massive datasets efficiently
- Use SQL and Python extensively for data manipulation and pipeline development
- Integrate infrastructure as code practices, including Terraform, to manage cloud resources
- Ensure data solutions follow CI/CD principles and cloud security standards
- Collaborate with engineers, analysts, and business stakeholders to align technical outcomes with organizational needs
What We're Looking For
- Proven track record in data engineering with strong experience in Azure-based ecosystems
- Deep familiarity with Snowflake, including data modeling and performance tuning
- Hands-on expertise in Databricks using PySpark or Spark SQL
- Solid understanding of ETL/ELT automation, data pipeline design, and cloud data platforms
- Proficiency in SQL and Python for data processing and scripting
- Experience applying modern data engineering practices in scalable cloud environments
- Fluency in English, both written and spoken
- Familiarity with Terraform or other infrastructure-as-code tools is highly valued
