Senior Data Engineer

Sterling B2B Developer Role: Senior Data Engineer Location: Dallas, TX or Mountain View, CA Duration: Long Term Contract As 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 Day Partner with Data Science, Product, and Engineering to collect requirements to define the data ontology for Mail Data & Analytics Lead and mentor junior Data Engineers to support Mail's ever-evolving data needs Design, build, and maintain efficient and reliable batch data pipelines to populate core data sets Develop scalable frameworks and tooling to automate analytics workflows and streamline users interactions with data products Establish and promote standard methodologies for data operations and lifecycle management Develop 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 stacks Create 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 issues Prototype new metrics or data systems Define and manage Service Level Agreements for all data sets in allocated areas of ownership Develop complex queries, very large volume data pipelines, and analytics applications to solve analytics and data engineering problems Collaborate with engineers, data scientists, and product managers to understand business problems, technical requirements to deliver data solutions Engineering consulting on large and complex data lakehouse data Must Have BS in Computer Science/Engineering, relevant technical field, or equivalent practical experience, with specialization in Data Engineering 8+ 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 Hermitage Infotech