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Common Data Engineer title, mid-level (3-5 years) and broad applicant pool increase competition.
Core data engineering skills are transferable, but Snowflake and Azure specialization increases industry specificity.
Explicit 3-5 years plus mandatory Snowflake and Azure/ADF/Synapse requirements raise shortlisting strictness.
Design, develop, and optimize ETL processes for efficient data extraction, transformation, and loading into data warehouses.
Collaborate with data architects and analysts to define data requirements and ensure data quality for reporting and analytics.
Monitor and resolve ETL job issues, maintain ETL workflows, and participate in data modeling and database design.
Bachelor’s degree in computer science, Information Technology, or related field.
3 to 5 years of experience as an ETL Developer or similar role.
Mandatory experience with ETL tools such as Azure Data Factory (ADF), Synapse, and Snowflake.
Proficient in SQL; experience with Azure Data Lake, Azure Blob storage, and Snowpark; multi-cloud experience is a plus.
Deep expertise in Azure data stack technologies including Azure Data Lake, Data Factory, Synapse, and Azure Storage.
Hands-on proficiency with Snowflake and Snowpark for cloud data warehousing solutions.
Experience working in Agile application development, support, and deployment environments with a focus on data engineering.