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Mid-level data engineer role with common SQL/ETL skills and moderate brand attracts medium competition.
Core data engineering skills are transferable, but Azure Databricks/DBT specificity raises sensitivity to domain fit.
Mandatory 5+ years and required Databricks/Azure/DBT/SQL skills make screening strict.
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Design, develop, and maintain Business Translation Layer (BTL) pipelines using SQL and DBT in Azure Databricks.
Create and manage build and release pipelines for Databricks using Azure DevOps or Harness.
Monitor performance of BTL jobs, diagnose data processing issues, and implement performance improvements.
Minimum 5 years of experience with data warehousing concepts and software development involving large data sets using SQL.
Hands-on experience in designing and developing data transformation logic with SQL and working with Databricks.
Knowledge of Azure cloud platform including Azure Synapse and ADLS, plus experience with GitHub and build management.
Work Experience Required: Minimum 5 years in relevant data engineering roles.
Experienced in building and optimizing large-scale data pipelines integrating within complex system architectures.
Strong expertise in distributed computing concepts and secure coding practices for data pipeline development.
Comfortable working in Azure cloud environments, managing end-to-end data transformation workflows and collaborating across multiple teams.