Jobs / United States / Datadog INC

Datadog INC

Staff Software Engineer - Watchdog Anomaly Detection

New York, New York, USA Posted today

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Skills this job asks for

Machine learningLeadershipKafkaPython

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 64 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Datadog INC paid sponsored hires in similar roles22 certified filings for “Senior Software Engineer” (Software Developers) in NY: $205k–$245k, median $225k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 64 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Datadog INC paid sponsored hires in similar roles
22 certified filings for “Senior Software Engineer” (Software Developers) in NY: $205k–$245k, median $225k. Most were filed at wage level IV (73%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

Datadog is looking for a Staff Software Engineer to help shape the future of our anomaly detection platform. Our team builds and operates high-scale distributed systems that process streaming and batch data, working alongside machine learning systems to automatically identify potential issues in our customers' environments. As we expand these capabilities across Datadog's products, you'll play a key role in defining the technical direction, evolving our architecture, and building systems that surface meaningful insights to customers without requiring manual configuration. This is an opportunity to solve complex engineering challenges at scale while influencing the direction of a platform that powers critical customer experiences. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: • Lead the architecture and evolution of large-scale distributed systems that power automated anomaly detection across Datadog's platform. • Design and improve high-throughput streaming and batch processing pipelines, enabling timely and reliable detection of potential issues in customer environments. • Drive technical initiatives to simplify, consolidate, and modernize existing systems, improving scalability, maintainability, and operational efficiency. • Partner with engineering leaders, product managers, and data scientists to define the long-term technical strategy for anomaly detection and its integration with alerting capabilities. • Shape how anomaly detection capabilities are delivered across Datadog products, helping customers identify meaningful issues without requiring manual configuration. • Provide technical leadership across engineering teams, influencing architectural decisions and aligning solutions with broader product and platform goals. Who You Are: • You have extensive experience designing, building, and operating large-scale distributed systems, particularly high-throughput or data-intensive backend platforms. • You have a strong understanding of streaming and batch processing architectures, including the challenges of processing large volumes of data with low latency. • You have experience leading complex architectural initiatives, making technical tradeoffs, and improving the reliability and maintainability of production systems. • You can drive technical strategy beyond your immediate team, collaborating with engineering leaders and product partners to translate customer needs into scalable platform solutions. • You are comfortable working across technologies and learning new systems; experience with technologies such as Flink, Kafka, Cassandra, Go, or Python is a plus. • You bring a product-oriented mindset and can connect technical decisions to customer outcomes; familiarity with machine learning systems or deploying models in production is a plus, but not required. Benefits and Growth: • Opportunities to grow as a technical leader while influencing the architecture and direction of shared capabilities used across Datadog products. • Exposure to complex engineering challenges involving large-scale distributed systems, real-time data processing, and machine learning. • Collaboration with experienced engineers, product managers, and data scientists across multiple teams. • Opportunities to develop expertise in platform architecture, technical strategy, and cross-functional engineering leadership. • A collaborative engineering environment that encourages knowledge sharing, continuous learning, and professional development. Benefits and Growth listed above may vary based on the country of your employmen

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