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Mid-level, generalist Data Engineer role with common Azure/Databricks skills attracts high applicant density.
Azure/Databricks and enterprise governance skills are transferable but favor platform-specific experience.
Explicit 4–6 years plus mandatory Azure, Databricks, SQL, and governance skills enforces strict shortlisting.
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Design and implement scalable data pipelines and analytics solutions using Azure services.
Develop and maintain data models, ETL processes, data integration workflows, and ensure data quality, governance, and security across analytics platforms.
Collaborate with data scientists, analysts, and business stakeholders to support decision-making through dashboards, visualizations, and deployment of machine learning models.
Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
4-6 years of experience in data engineering.
Hands-on experience with Azure Data Factory, Azure Databricks, Azure Data Lake, and Microsoft SQL Server.
Experience developing and maintaining data governance and security frameworks within Databricks and enterprise data warehouse ecosystems.
Experienced in collaborative development workflows including version control (e.g., GitHub) and co-development of models and analytics projects.
Strong technical expertise within the Azure ecosystem covering data engineering, ETL, data warehousing, and big data storage solutions.
Ability to leverage data to make strategic recommendations and clearly communicate findings to business stakeholders.