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Mid-level Data Engineer with common cloud/Databricks/Spark skills and metro setting creates high competition.
Core data engineering skills are broadly transferable across industries despite AEC domain context.
Explicit 3-year requirement plus mandatory Azure/Databricks/Spark/Python skills yields medium strictness.
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Design, develop, and automate ETL/ELT data pipelines and workflows to support Architecture, Engineering and Construction (AEC) initiatives.
Optimize and manage data storage solutions such as data lakes and warehouses for scalability and performance within Microsoft Azure environment.
Collaborate with Data Scientists and AI engineers to deliver reliable data solutions enabling advanced analytics and AI/ML capabilities.
Bachelor's degree or equivalent experience in a related field.
Minimum 3 years of related data engineering experience.
Proficiency with Microsoft Azure services including Azure Data Factory, Databricks, and Synapse Analytics.
Experience developing data pipelines and programming in Python and SQL.
Experienced with modern data engineering frameworks such as Apache Spark and Databricks, with knowledge of Lakehouse architectures.
Comfortable working in Agile environments following SDLC and DevOps practices for data solutions.
Skilled in ensuring data quality, governance, security compliance, and pipeline observability in large-scale enterprise cloud environments.