Big Data Platform & Distributed Systems (Mid/Senior/Lead/Principal)

Benefits

Parental leave

26 weeks Source: https://careers.salesforce.com/en/salesforce-stories/wellbeingbenefits/the-benefits-of-parenthood-how-salesforce-supports-growing-families/. source Last checked May 7, 2026.

Non-birth-parent leave

12 weeks Source: https://careers.salesforce.com/en/salesforce-stories/wellbeingbenefits/the-benefits-of-parenthood-how-salesforce-supports-growing-families/. source Last checked May 7, 2026.

Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

Not verified

Relocation assistance

Not verified

Childcare support

Not verified

Learning budget

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Verification

Source-linked last checked May 7, 2026

Salary

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401(k) match

Listed Source: EMPLR_CONTRIB_INCOME_AMT. source Last checked May 7, 2026.

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Schedule

Shift type

Not verified

Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Big Data Platform & Distributed Systems (Mid/Senior/Lead/Principal) Washington - Bellevue About the Teams: By applying to this role, you will be considered for two mission-critical teams at the heart of our data strategy. Both teams operate at extreme scale, leveraging Public Cloud (AWS/GCP) and Kubernetes to power the next generation of data-driven intelligence. Pillar 1: Data Engineering & Observability Build and own large-scale data pipelines and observability systems that power metrics, logging, and real-time insights across services. This role focuses on designing reliable telemetry pipelines, improving monitoring and alerting, and ensuring data quality and system visibility at scale. Ideal candidates have strong distributed systems fundamentals, backend development experience (Java or similar), and experience operating high-throughput data or monitoring platforms in cloud or hybrid environments. Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow by pushing the boundaries of AI development tools to deliver secure, optimized, and high-quality code. Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale. Pillar 2: Data Cloud. Big Data Compute platform team. Owns the compute infrastructure that powers large-scale Spark workloads. The team focuses on optimizing core Spark performance, solving distributed systems challenges, and building scalable AI infrastructure, including exploring efficient ways to run smaller language models. Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably. Critically evaluate

Read the full description at careers.salesforce.com. FewerJobs shows a source-linked preview and links to the original posting.