Data Engineer
Responsibilities:
• Build and support scalable data pipelines using Python, including PySpark, within Azure Synapse Analytics notebooks and pipeline workflows.
• Design, load, and maintain warehouse structures in a massively parallel processing environment, applying dimensional modeling concepts such as facts and dimensions.
• Ingest and transform data from a range of sources, including APIs, databases, and flat files, to create dependable datasets for downstream use.
• Improve the efficiency and reliability of Azure Synapse processes by tuning queries, refining workloads, and addressing performance constraints.
• Partner with data architects, analysts, and other stakeholders to translate business needs into practical data models and engineering solutions.
• Establish validation routines and data quality controls to promote completeness, consistency, and accuracy across datasets.
• Monitor scheduled jobs and pipeline activity, troubleshoot failures, and implement corrective actions to maintain service levels.
• Document data flows, transformation logic, technical configurations, and operating procedures to support maintainability and knowledge sharing.
• Apply security, privacy, and governance standards to data solutions while supporting broader data platform initiatives such as lakes, lakehouses, and cataloging practices.
Qualifications:
Compensation
$100,000.00-$150,000.00 YearlyAbout Us
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