Back
Remote role, popular mid-level Data Engineer title, and known employer increase applicant competition.
Core data engineering skills transfer across industries though Azure/Snowflake and banking preference raise specificity.
Multiple mandatory Azure/Databricks/Snowflake/Python/CI-CD requirements create strict technical filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and maintain scalable data pipelines and ETL processes using Azure Data Factory, Databricks, and related Azure services.
Optimize data storage and workflows including Azure Data Lake, Azure SQL Database, Snowflake, SQL, and Python for performance and scalability.
Collaborate with cross-functional teams to translate business requirements into technical solutions, ensuring data quality, security, and governance.
Bachelor’s degree in Computer Science, Information Technology, or a related field.
Strong experience with Azure data services including Azure Data Factory, Azure Data Lake, Databricks, and Snowflake.
Proficiency in Python and SQL for data processing and transformation; experience with ETL/ELT and data pipeline design.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced with cloud data engineering on Azure platforms, with solid knowledge of data warehousing, OLAP and data modelling concepts.
Familiarity with CI/CD pipelines, DevOps practices, and governance for scalable and secure cloud data architecture.
Exposure to agile methodology and preferably experience in banking domain projects and Microsoft Azure certification (e.g., Azure Data Engineer Associate).