Data Engineer

Sterling B2B DeveloperRole: Senior Data EngineerLocation: Dallas, TX or Mountain View, CADuration: Long Term ContractAs part of the Mail Analytics Data Engineering team, you will be working on large-scale batch pipelines, data serving, data lakehouse, and analytics systems, enabling mission critical decision making, downstream, AI-powered capabilities, and more. If you're passionate about building data infrastructure and platforms that power modern Data- and AI-driven business at scale, we want to hear from you!Your DayPartner with Data Science, Product, and Engineering to collect requirements to define the data ontology for Mail Data & AnalyticsLead and mentor junior Data Engineers to support Mail's ever-evolving data needsDesign, build, and maintain efficient and reliable batch data pipelines to populate core data setsDevelop scalable frameworks and tooling to automate analytics workflows and streamline users interactions with data productsEstablish and promote standard methodologies for data operations and lifecycle managementDevelop new or improve and maintain existing large-scale data infrastructures and systems for data processing or serving, optimizing complex code through advanced algorithmic concepts and in-depth understanding of underlying data system stacksCreate and contribute to frameworks that improve the efficacy of the management and deployment of data platforms and systems, while working with data infrastructure to triage and resolve issuesPrototype new metrics or data systemsDefine and manage Service Level Agreements for all data sets in allocated areas of ownershipDevelop complex queries, very large volume data pipelines, and analytics applications to solve analytics and data engineering problemsCollaborate with engineers, data scientists, and product managers to understand business problems, technical requirements to deliver data solutionsEngineering consulting on large and complex data lakehouse dataMust HaveBS in Computer Science/Engineering, relevant technical field, or equivalent practical experience, with specialization in Data Engineering8+ years of experience building scalable ETL pipelines on industry standard ETL orchestration tools (Airflow, Composer, Oozie) with deep expertise in SQL, PySpark, or scala.5+ years leading data engineering development directly with business or data science partners