> Markdown version of [/jobs/ext/1505682-senior-data-engineer](https://www.wearedevelopers.com/jobs/ext/1505682-senior-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer - **Company:** Yahoo - **Location:** Richardson, TX, United States - **Experience:** Expert - **Salary:** $128,250.0 - $266,875.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, BigQuery, Program Optimization, Continuous Integration, Data Governance, Extract Transform Load (ETL), Data Systems, DevOps, Data Flow Control, Machine Learning, Apache Oozie, DataOps, Cloudera, SQL Databases, Google Cloud, Delivery Pipeline, Yahoo Mail, Pyspark, Information Technology, Looker Analytics, Data Pipelines - **Published:** July 30, 2026 - **Apply:** https://www.jofdav.com/jobs/59037825-senior-data-engineer ## About the Role * Education: BS/MS in Computer Science, Engineering, or a relevant technical field. * Experience: 6+ years of experience building scalable ETL/ELT pipelines using industry-standard orchestration (Airflow, Composer, or Oozie). * Technical Mastery: Deep expertise in SQL, PySpark, or Scala. * Scale: Proven track record of managing Multi-Terabyte/Petabyte datasets and solving large-scale challenges (e.g., skew mitigation, data sketches, and accumulation patterns). * Cloud & DevOps: Professional experience with at least one major cloud provider (GCP, AWS, or Azure) and a strong command of GitOps workflows (CI/CD, PRs). * Compliance: Experience working within GDPR and other data privacy frameworks. * Soft Skills: Exceptional communication skills with the ability to prioritize tasks in a high-pressure, fast-paced environment. Preferred Qualifications * GCP Expertise: 3+ years of experience with Google Cloud Platform (BigQuery, Dataproc, Dataflow, Composer, Looker). * AI/ML Alignment: Experience building data features specifically optimized for Machine Learning models and AI applications. The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies ; exercising sound judgment ; working effectively, safely and inclusively with others ; exhibiting trustworthiness and meeting expectations ; and safeguarding business operations and brand integrity. ## Description You are a Senior Data Engineer who thrives on complexity and scale. You don't just build pipelines; you define the data ontology for the entire Mail organization. You are a strategic thinker who can influence event instrumentation at the source while collaborating with Data Science and ML teams to deliver high-impact analytics., * Architect: Partner with Data Science, Product, and Engineering to define the global data ontology for Yahoo Mail and lead the technical roadmap for core datasets. * Build Scalable Systems: Design, build, and maintain high-reliability batch and streaming data pipelines that populate our mission-critical data lakehouse. * Innovate Tooling: Develop automated frameworks and self-service tools that streamline how users interact with data products across the company. Leveraging autonomous AI agents and AI Tooling. * Data Governance: Establish standard methodologies for data operations, lifecycle management, and strict SLA management for all datasets within your ownership area. * Optimize Performance: Improve existing large-scale data infrastructures by applying advanced algorithmic concepts to optimize code and underlying data system stacks. * Collaborate: Act as a data consultant for complex cross-functional projects, ensuring integrated solutions across Mail engineering teams. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [The Golden Age of Email: Owning the Inbox in the Age of AI](https://www.wearedevelopers.com/videos/100128-the-golden-age-of-email-owning-the-inbox-in-the-age-of-ai) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know)