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Mid-level generalist data engineer role with common skills, producing moderate candidate competition.
Core data engineering skills are broadly transferable, though AEC domain knowledge is beneficial.
Explicit 3-year requirement plus mandatory Azure/Databricks and Spark skills increase filter selectivity.
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Design, develop, and automate scalable data pipelines and workflows (ETL/ELT) to integrate data from various sources into target systems.
Optimize and manage data storage solutions such as data lakes and warehouses for performance, scalability, and data quality.
Collaborate with Data Scientists, AI engineers, and stakeholders to provide reliable data solutions supporting advanced analytics, AI/ML, and business insights.
Bachelor's degree or equivalent directly related experience considered in lieu of a degree.
Minimum 3 years of related work experience in data engineering or similar roles.
Proficiency in Microsoft Azure data services including Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
Strong programming skills in Python and SQL; experience with Apache Spark, Databricks, and modern data frameworks.
Experienced in working with modern Lakehouse architectures and enterprise-scale cloud data platforms, especially Databricks.
Familiar with supporting data pipelines that enable advanced analytics and AI/ML solutions within AEC or similarly complex business environments.
Skilled in building reliable, performance-optimized, scalable data engineering solutions within Agile and SDLC frameworks.