Hiring: Senior Data Engineer Company: Fractal Location: San Francisco Bay Area Job Posted Time: 2026-09-10 07:38:45 Employment Type: Full-time / Hybrid Target Skills & Keywords : A/B Testing, Agile, CI/CD, Data Lake, Data Pipeline, Data Warehouse, Docker, ELT, ETL, Feature Store, Git, HDFS, Hadoop, Helm, Jenkins, Kubernetes, Linux, Machine Learning, Python, Redshift, Snowflake, TestNG, containerd About the job Experience: •10+ years of software development and data engineering experience with very high proficiency in Python (production-grade: packaging, testing, CI/CD). Required Skills: •One of our well-known clients, a leading global digital retail and e-commerce organization, is seeking a Senior Data Engineer to design, build, and operate large-scale, production-grade data platforms that power analytics and data science across the Retail Online organization. •The ideal candidate is not just a strong technologist. They are a delivery-minded engineer who can manage cross-functional programs, enforce rigorous QA and observability standards, translate complex methodologies into actionable insights, and keep mission-critical pipelines reliable, scalable, and cost-efficient. •Project Management •Cross-Functional Scoping & Dependency Governance — Plan project scope, timelines, and dependencies across Data Science, Analytics, and Business teams. Track critical paths and coordinate deliverables to ensure continuous, seamless delivery. •Stakeholder Alignment & Executive Reporting — Maintain project tracking artifacts and status dashboards. Prepare and deliver executive roadmap updates, milestone progress, and risk mitigation summaries to leadership. •Global Team Coordination & Technical Hand-offs — Direct coordination with offshore engineering teams. Align on technical designs, enforce development standards, and lead structured code and documentation reviews. •Delivery Governance & SLA Accountability — Define delivery milestones, manage scope changes, and enforce operational SLAs. Lead cross-team incident escalations and post-incident reviews to maintain execution quality. •Analytics Execution Management Qualifications: •Detailed knowledge of and substantial experience with data structures and algorithms. •Solid technical database knowledge across Hadoop, Python, and Snowflake — data modeling, performance tuning, cost governance, and large-scale query optimization. •Hands-on Kubernetes experience — deploying data workloads, managing namespaces, debugging pods/logs/events, and tuning resource requests and limits. •Proficiency with Docker — authoring Dockerfiles, multi-stage builds, container registries, and integrating images into orchestration and CI/CD pipelines. •Applied hands-on capability in Tableau (published data sources, extract schedules, performance optimization). •Applied hands-on capability in a Unix/Linux environment. •Demonstrated capacity to present complex ideas in a clear, concise way to both technical and non-technical audiences. •BS in Computer Science, Engineering, Mathematics, Statistics, Econometrics, or other quantitative field. •Preferred: MS in Computer Science, Engineering, Statistical Methods, or Machine Learning. Compensation: •$110,000 - $145,000 / year •Flexible work environment (work from home / hybrid options) •In addition, for the current performance period, you may be eligible for a discretionary bonus Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!