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Remote, mid-level Data Engineer role with common skillset and title increases applicant competition.
Azure/Databricks specialization makes skills moderately transferable across industries.
Multiple mandatory Azure, Databricks, and data modeling requirements make shortlisting highly selective.
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Design, develop, and optimize ETL data pipelines using Azure Data Factory (ADF).
Build and maintain scalable data processing solutions within Databricks environment using Spark.
Implement and manage efficient data models, ensuring performance in cloud-based Azure systems.
6+ years of professional experience in data engineering or related roles.
Strong hands-on experience with Azure Data Factory, Databricks, and Data Modeling (including OLAP, OLTP, dimensional models).
Proficiency in SQL, NoSQL databases, and programming languages such as Python, SQL, or Scala.
Strong understanding of Azure Cloud services including Synapse, Storage, and experience with Apache Spark.
Experienced in building and optimizing large-scale, cloud-based data pipelines with measurable performance improvements.
Able to collaborate effectively with cross-functional teams including data scientists and business stakeholders, translating complex data requirements into technical solutions.
Comfortable working with end-to-end data workflows including data transformation, integrity, security, and compliance in Azure environments.