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Job Description & How to Apply Below
Design and Execute
• Partner with data product managers to gather and deliver data pipelines.
• Design ETL solutions including data quality, data security, and data pipeline resiliency.
• Execute ETL solutions including data security, data quality and performance requirements.
Data Extraction, Load and Transformation
• Design, build and implement ELT pipelines to efficiently ingest and transform data from a wide variety of data sources and deliver datasets that meet business requirements.
• Optimize performance for large datasets and data workflows for performance, scalability, and reliability to support business needs.
• Develop and maintain scalable data pipelines leveraging Azure Synapse, PySpark, APIs, and SQL & performing advanced data cleaning, transformation, and manipulation to ensure high-quality, and reliable data flows.
• Implement CI/CD processes to streamline and automate data pipelines deployment
• Apply data validation frameworks (Great Expectations, Fabric-native tools) to maintain accuracy
• Utilize partitioning, indexing, clustering strategies to enhance query performance
Process Improvement, Performance and Cost optimization tuning
• Collaborate with Data Science, AI, and Data product teams to optimize performance and cost effectiveness of their solutions.
• Identify and support the design of internal process improvements, including automating manual processes, optimizing data product delivery, and redesigning solutions for enhanced scalability.
• Implement solution adjustments to improve performance and cost-effectiveness of data products.
Issue Resolution and Support
• Monitor and troubleshoot the data pipelines proactively, which includes leading the support of data-related product pipeline issues to resolve data errors.
• Provide expert-level support and guidance to data teams across the Enterprise.
Desired Candidate Profile :
Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Analytics/Science, or related field
Microsoft Certified:
Azure Data Engineer (DP203)
or Microsoft Certified:
Fabric Data Engineer Associate or related cloud technologies, Fabric IQ/Databricks certifications a plus
8+ years of data engineering experience.
Demonstrated ability coding in one or more languages (PySpark preferred).
Experience with building data pipelines.
Experience with knowledge graphs a plus.
Demonstrated ability to manage multiple priorities simultaneously.
Demonstrated ownership of production-grade pipelines.
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