{"id":1987098,"url":"https://alion.io/job/netapp-director-software-engineer-customer-success","title":"Director, Software Engineer, Customer Success","company":{"id":58700,"name":"NetApp","domain":"netapp.com","url":"https://alion.io/company/netapp","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"A","score":90,"open_postings":26,"ghost_share":0,"stale_share":0.385,"repost_share":0,"time_to_fill_p50_days":54,"computed_at":"2026-10-12T06:55:09Z"}},"role":"Leadership","role_family":"Leadership","seniority":"head","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Jose, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":266000,"max_usd":498000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":2192},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"Machine Learning","optional":false},{"name":"Ray","optional":false},{"name":"Spark","optional":false}],"status":"live","first_seen_at":"2026-09-19T22:54:02Z","employer_posted_date":"2026-10-06","last_verified_at":"2026-10-12T16:47:43Z","board_verified":true,"closed_at":null,"days_open":22,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":22},"description":"Job Summary\nDataPelago is at the forefront of revolutionizing data processing for traditional analytics and cutting-edge GenAI preprocessing. We are building an innovative data processing engine that is transforming how Apache Spark, Apache Flink, Ray and others operate on diverse, large-scale data. Our team of engineers drive and adopt advances in hardware-accelerated computing, parallel processing of large-scale data, query optimization, distributed systems, compilers, machine learning, and cloud-native computing. We are looking for specialists to join our engineering team and shape the future of accelerated data processing.\nDataPelago Nucleus is a universal data processing engine that is designed to accelerate the processing of diverse data - structured through unstructured - with any parallel processing framework - e.g., Apache Spark - on any infrastructure - including vectorized CPU and GPU. DataPelago Accelerator for Spark (DPA-S), our product based on DataPelago Nucleus, is running large-scale production applications of many globally renowned customers.\nThe Opportunity:\nAs a Senior/Principal Data Processing Engineer - OSS, you will be a key individual contributor in adopting and advancing capabilities of open-source software (OSS) platforms such as Apache Gluten, Velox, Apache Spark, and Apache Flink in the context of DataPelago’s data processing engine. You will enhance functional breadth, performance, scale, and reliability of the DataPelago engine through downstream and upstream contributions. You will have the opportunity to engage with community working on these platforms. This is a unique opportunity to make a significant impact on a category-defining product and work with a talented team of engineers.\nWhat You'll Do:\nLead and grow a talented team of engineers with expertise in the development, operations, tuning, and support of data engineering, data preparation, and analytics applications leveraging massively parallel data processing platforms.\nDrive development with technical leads to implement and deliver industry-leading automated and AI-assisted capabilities for product validation, diagnosing functional and performance anomalies, tuning and optimizing applications for DataPelago’s data processing platform.\nEnsure customer success in their deployment and usage of DataPelago data processing platform through comprehensive preventive, proactive, and responsive product validation and product support.\nEngage customers across their adoption lifecycle.\nEstablish metrics including for product quality and support quality; lead the team in ensuring these metrics are continuously improved and achieved in customer deployments.\nContinuously improve software development lifecycle practices leveraging the latest AI advances for higher code quality, release velocity, and productivity.\nExecute efficiently to meet customer success objectives, aligned with organization goals and priorities.\nLead by example and foster a high-performance, high-integrity, collaborative work culture.\nCollaborate and partner effectively with other engineering, product management, customer success, and sales teams.\nWhat You'll Bring:\nBachelor’s degree in computer science or a related field. Master’s preferred.\n12+ years of production software development and support experience with 5+ years of experience managing enterprise software support.\n10+ years of experience in developing and supporting data processing pipelines for applications such as data engineering, data preparation, and analytics platforms and their underlying data processing platforms for customer production deployments. Experience with Apache Spark based products and pipelines preferred.\nTrack record of stellar customer support; deep experience in managing support teams, tools, and processes for global enterprise software support.\nTechnical and process rigor in validating data accuracy, high performance, reliability, and security capabilities of enterprise data processing products or pipelines.\nAbility to attract, retain, and grow exceptional talent in data processing platform and pipeline development, validation, and support.\nSolid understanding of the architecture, deployment, and operations of data processing products and pipelines in the cloud - in SaaS, VM-based, container-based, and serverless scenarios. Experience with GCP, AWS, and their Apache Spark related offerings preferred.\nExcellent judgment on data product validation, enterprise software support, AI adoption, and people management. 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