Netflix · 2 days ago
Distributed Systems Engineer (L6) - Commerce Product Data Engineering
United States
Full-time
Remote
Lead/Staff
$230K/yr - $960K/yrNetflix is one of the world's leading entertainment services, and they are seeking a Distributed Systems Engineer to provide strategic technical leadership across their Machine Learning data ecosystem. The role involves architecting and building distributed data systems, driving the technical vision for ML-oriented data products, and ensuring high reliability and observability of ML-critical data systems.
Digital EntertainmentMedia and EntertainmentTVVideo Streaming
Responsibilities
Lead the technical vision for ML-oriented data products
Drive the strategy for how we produce, manage, and deliver data for feature computation, model training, online inference, feedback loops, and model evaluation across the Commerce ecosystem
Identify cross-team opportunities to improve ML data availability, consistency, lineage, observability, and reliability
Architect and build distributed data systems at scale
Design and implement batch + real-time pipelines, event-driven data products, and multi-tenant distributed systems using Spark, Flink, Kafka, and other core Netflix frameworks
Shape the next generation of ML-ready datasets powering a broad spectrum of usecases across Commerce
Partner deeply with Platform teams
Work closely with ML Platform to ensure feature stores, training pipelines, and inference paths are supported with correct freshness, quality, and service-level guarantees
Influence and collaborate on platform primitives that improve the ML developer experience across the end-to-end lifecycle
Be the connective tissue between ML needs and data/system design
Translate ML requirements (latency, accuracy, consistency, backfillability, reproducibility) into data architecture decisions
Proactively unblock ML partners by evolving data products, schema design, transport mechanisms, and low-latency interfaces
Drive reliability, observability, and operational excellence
Ensure ML-critical data systems meet high SLAs through strong observability, real-time alerting, debugging pipelines, and root-cause analysis
Champion best practices for quality, reliability, testability, and automation across data products that operate 24x7
Provide technical mentorship and influence
Act as an engineering force multiplier across Commerce Data Engineering and partner teams
Shape technical direction, design reviews, standards, and long-term architectural choices that raise the performance of the entire ecosystem
Qualification
Required
You have a strong intuition about Data for ML. You understand feature computation, training/inference needs, offline/online consistency, and how data quality, latency, and drift impact model performance. You know how to apply your analytical skills and data engineering fundamentals to achieve the desired outcomes
You are proficient in at least one major language on the JVM stack (e.g., Java, Scala) and SQL (any variant). You strive to write elegant and maintainable code, and you're comfortable with picking up new technologies
You have hands-on distributed systems experience. You've built and operated large-scale, low-latency pipelines and services using technologies like Spark, Flink, Kafka, or equivalent frameworks
You are capable of designing and building well-modeled, high-quality data products and interfaces that are easy to discover, consume, and maintain
You are an excellent cross-functional communicator. You can translate ML, product, and engineering needs into clear technical direction and influence across teams as well as leadership on forward looking investments
You have a strong ownership mindset. You care deeply about reliability, observability, operational excellence, and the long-term health of the systems you build
You are comfortable with ambiguity. You thrive in fast-moving environments, make sound judgments with incomplete context, and elevate teams with clarity and direction
You relate to and embody many aspects of Netflix's Culture. You love working independently while also collaborating and giving/receiving candid feedback
Benefits
Health Plans
Mental Health support
A 401(k) Retirement Plan with employer match
Stock Option Program
Disability Programs
Health Savings and Flexible Spending Accounts
Family-forming benefits
Life and Serious Injury Benefits
Paid leave of absence programs
Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off
Full-time salaried employees are immediately entitled to flexible time off
Company
Netflix
Netflix is an online streaming platform that enables users to watch TV shows and movies.
Founded in 1997
10001+ employees
H1B Sponsorship
Netflix has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (310)
2024 (309)
2023 (191)
2022 (261)
2021 (268)
2020 (225)
Funding
Current Stage
Public CompanyTotal Funding
$63.91BKey Investors
Wells FargoTCVGroupe Arnault
2025-12-05Post Ipo Debt· $59B
2024-08-01Post Ipo Debt· $1.8B
2018-05-05Post Ipo Debt· $2.67M
Leadership Team
Gregory Peters
Co-CEO
Ted Sarandos
Co-CEO
Recent News
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