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Tier-1 brand, mid-level data engineer title, generalist skillset and broad requirements increase applicant competition.
Core data engineering skills are transferable, but financial domain and governance increase specificity.
Several explicit technical preferences and a 4+ years requirement create moderate hiring filters.
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Develop and manage business-critical data platforms with a focus on Google Cloud Platform, Big Data technologies, and ETL processes.
Deliver end-to-end data engineering solutions supporting global customer base and business analytics needs, including BI via Power BI stack.
Drive platform reliability and efficiency through continuous integration/delivery pipelines and automated release management tools.
Bachelor’s Degree in Computer Science, Computer Science Engineering, or related field required (advanced degree preferred).
4+ years of commercial software development experience.
Proficiency with Google Cloud Platform services (Google Cloud Storage, Big Query) and Big Data tools like Scala, Spark, Hive SQL.
Experience with ETL processes, Secure File Transfer operations, CI/CD pipelines including Maven, Salt, Git, Jenkins.
Experienced in designing and optimizing data models and business intelligence solutions, especially using Power BI with skills in DAX, Power Query, and SQL.
Strong understanding of web technologies, Unix/Linux environments, data structures, algorithms, and design patterns to enhance platform quality and performance.
Able to translate complex technical and business requirements into scalable, secure, and efficient engineering solutions within Agile development frameworks.