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Metro-based mid-level generalist data engineer with common skills increases applicant competition.
Core data-engineering skills transfer across industries, though platform-specific Azure/Fabric experience increases domain bias.
Explicit years, Azure/PySpark stack, production pipeline experience and certifications increase filtering strictness.
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Build and maintain scalable data pipelines integrating data from 2-5 source systems to support analytics and AI delivery.
Design, execute, and optimize ETL/ELT solutions ensuring data quality, security, performance, and cost-effectiveness, using Azure Synapse, PySpark, SQL, and APIs.
Provide expert-level support to data teams, troubleshoot pipeline issues, and implement process improvements including CI/CD for data pipeline deployment.
Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Analytics/Science, or related field required.
3-6+ years of data engineering experience required with demonstrated production-grade pipeline ownership.
Microsoft Certified: Azure Data Engineer (DP-203) OR Microsoft Certified: Fabric Data Engineer Associate OR related cloud certifications required.
No employment visa sponsorship upon hire or in the future as per company policy.
Experienced in designing and managing scalable, reliable data pipelines with strong coding ability in PySpark or similar languages.
Proficient in Azure Synapse, CI/CD implementation for data pipelines, data quality frameworks (e.g., Great Expectations), and performance tuning with partitioning/indexing.
Can multitask across priorities and collaborates effectively with data science, AI, and product teams to optimize data solutions.