What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Strong experience with Azure Cloud Platform services
- Proven expertise in Azure Data Factory for orchestrating and automating data pipelines
- Proficiency in SQL for data analysis and transformation
- Hands-on experience with Snowflake and SnowSQL for data warehousing
- Practical knowledge of DBT for transforming data in the warehouse
- Experience working in cloud-based data environments with large-scale datasets
- Bachelor’s degree in Data Engineering or a related field
- 8+ years of experience in data engineering roles using Azure and Snowflake
- Strong problem-solving communication and collaboration skills
Nice to have
- Technical leadership
- Mentorship
- Problem-solving
- Collaboration
- Cloud-native mindset
Day to day
- Design and develop robust ETL and ELT pipelines across Azure Data Factory Snowflake and DBT.
- Build reliable data integration workflows that move and transform data from multiple sources into Snowflake.
- Partner with stakeholders data analysts architects and DevOps teams to deliver scalable cloud-native data solutions while mentoring junior engineers.
