Back
Remote, mid-level popular data title, 5+ years band, and broad Azure/Databricks skill requirements.
Azure/Databricks specificity raises domain bias, but core data engineering skills remain transferable across industries.
Mandatory 5+ years plus required Azure/Databricks and ETL expertise increases filter rigidity.
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 solutions on Microsoft Azure, including data ingestion pipelines and storage mechanisms.
Collaborate with cross-functional teams to gather data requirements and support data scientists and analysts.
Monitor data pipelines ensuring data quality, governance, and smooth data flow.
Bachelor's degree in Computer Science, Engineering, or related field.
5+ years of experience with Big Data technologies.
Strong knowledge and hands-on experience with Microsoft Azure data services including Azure SQL Database, Azure Data Lake, Azure Blob Storage, and Azure Databricks.
Proficiency in data processing frameworks like Apache Spark, Hadoop, and ETL processes; programming experience in Python or Scala.
Experienced in real-world Azure data engineering projects with deep expertise in Azure Databricks and cloud-native data services.
Operational focus on end-to-end data pipeline management and cross-team collaboration for data-driven solutions.
Capable of implementing data governance and quality measures aligning with enterprise data engineering best practices.