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Tier-1 brand, popular Data Engineer title, mid-level experience, metro location, and broad Azure/Spark requirements.
Medium because core data engineering skills are transferable but Azure and energy-specific context increase specificity.
High due to explicit 5+ years requirement and mandatory Azure, Spark, and CI/CD skills.
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Design, develop, and maintain scalable, resilient data infrastructure and pipelines using Microsoft Azure technologies (Data Factory, Synapse, Databricks, Data Lake Storage).
Oversee entire data infrastructure for operational efficiency, scalability, and resiliency, including CI/CD deployment and maintenance of data solutions.
Collaborate with data scientists, analysts, and architects to deliver high-quality, validated data solutions and mentor junior data engineers.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
5+ years of proven experience as a Data Engineer or in similar role with data and ETL processes; total experience expected 3-6 years.
Strong expertise in Microsoft Azure data services: Azure Data Factory, Azure Synapse, Azure Databricks, Azure Blob Storage, Azure Data Lake Storage Gen 2.
Proficient in SQL for querying modern RDBMS; solid understanding of software engineering principles including CI/CD and version control.
Experienced in building and optimizing scalable data pipelines in Azure environments with emphasis on performance and reliability.
Hands-on with big data technologies like Spark and programming languages such as Python or Scala, with experience in PySpark preferred.
Ability to manage data engineering lifecycle including design, development, deployment, and troubleshooting within cloud-based, collaborative settings.