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Mid-level generalist data role with broad Azure/ETL requirements and metro appeal increases applicant density.
Data engineering skills like Azure, ETL and SQL are broadly transferable across industries.
Explicit 5+ years plus mandatory data-warehousing, Azure/ADF/Databricks, ETL tool and SQL requirements enforce strict filtering.
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Build and maintain data pipelines on MS Azure platform using Azure Data Factory and Data Bricks, supporting both structured and unstructured data sources.
Develop and support data warehousing solutions, including conceptual, logical, and physical data modeling, to enable business insights, reporting, and analytics.
Lead migration of on-premise data solutions to MS Azure and collaborate cross-functionally to resolve data-related technical issues and improve data solution best practices.
Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field.
Minimum 5 years of hands-on experience developing data solutions with strong data warehousing background (including Kimball dimensional design methodology).
Strong experience in MS SQL and ETL development tools such as Informatica or equivalent.
Recent development experience with MS Azure platform components including Databricks, Azure Data Factory (ADF), Kafka, Python (or R), Spark, and Change Data Capture (CDC).
Experienced in complex data pipeline architecture and migration projects within MS Azure ecosystem.
Technical operator comfortable with both hands-on development and advising on data modeling and database technologies.
Ability to collaborate effectively with internal technical stakeholders and business partners for operational reporting and analytics use-cases.