Sr Data Engineer

Location: Chicago or Dallas 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 You 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. ● 3+ years leading data engineering development directly with business or data science partners ● Built, scaled, and maintained Multi-Terabyte data sets and having an expansive toolbox for debugging and unblocking large scale analytics challenges (skew mitigation, sampling strategies, accumulation patterns, data sketches, etc.) ● Experience with at least one major cloud's suite of offerings (AWS, GCP, Azure). ● Developed or enhanced ETL orchestrations tools or frameworks ● Worked within standard GitOps workflow (branch and merge, PRs, CI / CD systems) ● Experience working with GDPR ● Self-driven, challenge-loving, detail oriented, teamwork spirit, excellent communication skills, ability to multitask and manage expectations Preferred ● MS/PhD in Computer Science/Engineering or relevant technical field, with specialization in Data Engineering ● 3+ years experience in Google Cloud Platform technologies (BiqQuery, Dataproc, Dataflow, Composer, Looker)