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Actively hiring, first seen by us todayYou will ensure the CPaaS data services roadmap balances immediate customer needs with long-term architectural sustainability and technical debt reduction.
Work in a geographically distributed team setup.
Open Source Leadership: Identify internal data platform technologies & contributions suitable for open-sourcing to establish Nutanix as a thought leader. Planning & Prioritization: Collaborate with engineering leads to define the high impact initiatives and quarterly priorities. You will ensure the CPaaS data services roadmap balances immediate customer needs with long-term architectural sustainability and technical debt reduction. Work in a geographically distributed team setup.
Planning & Prioritization: Collaborate with engineering leads to define the high impact initiatives and quarterly priorities. You will ensure the CPaaS data services roadmap balances immediate customer needs with long-term architectural sustainability and technical debt reduction. Work in a geographically distributed team setup. The role involves performing duties requiring the application of professional expertise and the exercise of independent judgment/discretion, creativity, problem-solving, and decision-making in carrying out responsibilities, as applicable to the position. The specific responsibilities of the role may vary based on business needs and role requirements. Employees can refer to the applicable guidelines and career frameworks for additional information regarding role expectations and responsibilities.
At Cloud Platform as a Service, our core mission is to architect, develop, and maintain a robust, enterprise-grade data and compute platform.
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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Day 0
Early. Similar jobs usually come down between day 5 and day 54.
From 10,704 similar postings that came down. Coming down is not always a hire.
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- Deep Systems Expertise: 12+ years of experience building and scaling large-scale software, with a specialized focus on distributed systems and database internals. You should have a proven track record of solving complex problems at the infrastructure layer. - Polyglot Programming: Expert-level proficiency in Go, C++, or Rust. You are also comfortable using Python to automate, prototype, and bridge services within a cloud-native ecosystem. - Data Engine Mastery: A deep, internal understanding (indexing, storage engines, data models, query optimization) of diverse data architectures:
- Data Engine Mastery: A deep, internal understanding (indexing, storage engines, data models, query optimization) of diverse data architectures: - Analytical & Time-Series: ClickHouse, Prometheus, VictoriaMetrics. - Relational: PostgreSQL, MySQL.
- Graph: Neo4j, Dgraph. - Messaging: NATS, Apache Kafka. - Cloud-Native Foundations: A solid architectural understanding of Kubernetes and container orchestration, specifically regarding stateful workloads and high-availability data services.
- Messaging: NATS, Apache Kafka. - Cloud-Native Foundations: A solid architectural understanding of Kubernetes and container orchestration, specifically regarding stateful workloads and high-availability data services. - Operational Excellence: Experience operating distributed "Big Data" systems in a resource constrained on-prem or hybrid cloud environment. You understand the nuances of observability, backup/restore, disaster recovery, and zero-downtime migrations.
- Analytical & Time-Series: ClickHouse, Prometheus, VictoriaMetrics. - Relational: PostgreSQL, MySQL. - Graph: Neo4j, Dgraph.
- Relational: PostgreSQL, MySQL. - Graph: Neo4j, Dgraph. - Messaging: NATS, Apache Kafka.
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
The role involves performing duties requiring the application of professional expertise and the exercise of independent judgment/discretion, creativity, problem-solving, and decision-making in carrying out responsibilities, as applicable to the position. The specific responsibilities of the role may vary based on business needs and role requirements. Employees can refer to the applicable guidelines and career frameworks for additional information regarding role expectations and responsibilities.
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Your Role - Architect & Innovate: Lead the design, implementation and optimization of core data platform components for on-prem, hybrid-cloud enterprise & service provider environments. You will ensure our systems are resilient, performant, scalable and easily "day-2 manageable" across diverse customer data centers, including air-gapped and highly regulated environments. - Performance Engineering: Dive deep into I/O stacks, memory management, DB engines, distributed messaging stack, and data models to squeeze every ounce of performance out of the hardware.
- Cloud-Native Foundations: A solid architectural understanding of Kubernetes and container orchestration, specifically regarding stateful workloads and high-availability data services. - Operational Excellence: Experience operating distributed "Big Data" systems in a resource constrained on-prem or hybrid cloud environment. You understand the nuances of observability, backup/restore, disaster recovery, and zero-downtime migrations. - AI-Augmented Engineering: A forward-thinking passion for integrating AI tools into the SDLC. You have experience using AI for code generation, automated design reviews, and accelerating the path from "concept to commit."
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No clear work-authorization passage found. Eligibility is unconfirmed.