{"id":1168656,"url":"https://alion.io/job/hewlett-packard-enterprise-data-platform-analytics-architect","title":"Data Platform Analytics Architect","company":{"id":5292,"name":"Hewlett Packard Enterprise","domain":"hpe.com","url":"https://alion.io/company/hewlett-packard-enterprise","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":82,"open_postings":155,"ghost_share":0,"stale_share":0.91,"repost_share":0,"time_to_fill_p50_days":16,"computed_at":"2026-10-15T05:46:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":161000,"max":378000,"currency":"USD","period":"year","gross":null,"usd_annual":378000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon S3","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Oracle","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"Splunk","optional":false},{"name":"Teradata","optional":false},{"name":"Vertica","optional":false},{"name":"Apache Iceberg","optional":true},{"name":"Spark","optional":true},{"name":"Trino","optional":true}],"status":"live","first_seen_at":"2026-09-01T00:00:00Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-10-16T02:02:02Z","board_verified":true,"closed_at":null,"days_open":45,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":45},"description":"Data Platform Analytics ArchitectThis role has been designated as ‘Remote/Teleworker’, which means you will primarily work from home.Who We Are:\nHewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.\nJob Description:\nWe are seeking a highly strategic and technically grounded Data Platform Analytics Solutions Architect to help drive the next phase of growth for our X10K data platform business. This is a customer-facing architect role that leads with a data and workload-first perspective, focusing on how enterprise data is ingested, stored, processed, queried, governed, and consumed across modern analytics environments.\nThe role will operate at the intersection of enterprise analytics, data architecture, modern data platforms, and infrastructure, helping customers modernize traditional data warehouse environments into more open, scalable, performant, and flexible data lake and data Lakehouse architectures.\nA major focus will be identifying and developing opportunities around analytics platforms such as Vertica, SingleStore, and Cloudera, while helping customers evaluate alternatives to traditional tightly coupled legacy Enterprise Data Warehouse platforms. The Architect will help customers understand where modern architectures that separate compute from data can improve scalability, economics, operational flexibility, and long-term data accessibility.\nYou will partner closely with customers, sales teams, solution architects, ISVs, and Product Management to design high-impact analytics solutions, develop migration and modernization strategies, and build repeatable go-to-market motions around X10K.\nA key aspect of the role is the ability to identify and prioritize the right opportunities based on workload characteristics, customer readiness, technical fit, scale, economics, and business objectives. The successful candidate must be able to move beyond infrastructure discussions and engage customers at the data architecture, database, analytics, and application level.\nThis is not a pure storage role. A strong understanding of storage and data infrastructure is important, but the architect must be able to position X10K as part of a broader enterprise data architecture and demonstrate how the data platform enables analytics modernization.\nKey Responsibilities\nData-Centric Analytics Architecture\nLead architecture discussions starting with the customer's data, applications, and analytics requirements, including:Data volumes, growth rates, velocity, and distribution\nStructured, semi-structured, and unstructured data\nData ingestion and transformation requirements\nQuery patterns and analytical processing requirements\nData locality, gravity, movement, and duplication\nData retention and lifecycle requirements\nBatch, streaming, and real-time analytics requirements\nConcurrency and performance expectations\n\nDesign modern analytics architectures by optimizing:Data ingestion and ETL/ELT pipelines\nCompute-to-data access patterns\nQuery performance and concurrency\nData placement and movement\nStorage and compute scalability\nOpen data access and interoperability\nData lifecycle and retention\nPerformance, reliability, and cost efficiency\n\nHelp customers evolve from infrastructure-centric architectures toward data-centric architectures where multiple analytics engines and applications can leverage common enterprise data assets.\nRecommend design optimizations that improve performance, scalability, operational simplicity, resiliency, and economics.\nData Warehouse Modernization\nLead technical assessments of traditional enterprise data warehouse environments, particularly:\nIdentify workloads and data sets that are strong candidates for modernization.\nAnalyze existing environments based on capacity, performance, ETL/ELT, concurrency, licensing and make informed recommendations and solution alternatives.\nDevelop modernization strategies that transition customers from traditional data warehouses toward modern analytical databases and data Lakehouse architectures.\nHelp customers determine which workloads should be migrated, modernized, consolidated, or retained.\nPartner with sales teams to create compelling competitive strategies for displacement opportunities.\nAnalytics Platform Architecture\nDevelop deep expertise in analytics and data platforms strategically aligned to X10K, including:Enterprise analytics and Lakehouse platforms such as Vertica, SingleStore, and Cloudera\nSearch, observability, and machine-data analytics platforms such as Splunk and Elastic\n\nArticulate the architectural differences between traditional shared-nothing data warehouses, distributed databases, cloud-native databases, data lakes, and Lakehouse architectures.\nHelp customers select the appropriate architecture based on workload requirements rather than simply replacing one infrastructure platform with another.\nWork with strategic software partners to develop validated solutions, best practices, reference architectures, sizing guidance, and repeatable deployment patterns.\nAnalytics Solution Architecture & Sizing\nScope and size enterprise analytics environments based on data volumes, size, ingest rate, retention, SLA, and other customer specific functional requirements.\nUnderstand how analytical database behavior impacts infrastructure requirements.\nAbilit to assess and establish realistic performance expectations across the complete analytics pipeline from data ingestion through transformation, query processing, and data protection.\nDevelop sizing methodologies that field architects and sales teams can use consistently across analytics opportunities.\nHelp customers design and adopt modern data lake and data Lakehouse architectures.\nArticulate the architectural and business benefits of separating enterprise data from individual compute and database platforms.\nUnderstand and articulate concepts including:S3/object-based data architectures\nOpen data formats\nOpen table formats\nSchema evolution\nMetadata and cataloging\nData governance\nData sharing\nData pipelines\nDistributed analytics\nCompute/storage separation\n\nPosition the data lake or Lakehouse as an enterprise data foundation, rather than simply another storage tier.\nHelp customers understand when separating compute from storage can provide architectural or economic advantages compared with tightly integrated database appliances.\nCustomer Engagement & Deal Leadership\nLead technical discovery sessions with enterprise customers to identify, shape, and qualify analytics modernization opportunities.\nTranslate business objectives into scalable analytics and data platform architectures.\nUnderstand both the technology and business drivers behind major data warehouse modernization initiatives.\nServe as a trusted advisor during complex architecture and platform transformation discussions.\nApply strong technical and commercial judgment to determine where X10K and associated analytics platforms are the right fit.\nMaintain credibility by clearly identifying where a proposed architecture does-and does not-align with customer requirements.\nMigration & Modernization Strategy\nHelp customers assess and build practical migration strategies for large-scale analytics environments.\nDevelop phased approaches that allow customers to modernize without requiring unnecessary \"big bang\" migrations.\nIdentify opportunities where new workloads, data growth, archive data, or adjacent analytics initiatives can provide an initial entry point into an incumbent/ legacy environment.\nHelp customers develop migration approaches that reduce technical and operational risk while creating a path toward a broader modern data architecture.\nCross-Functional Leadership\nPartner closely with Product Management to influence X10K analytics roadmap priorities, prioritize feature/functionality, and identify competitive gaps.\nPartner with engineering, performance teams, ISVs, and solution teams to validate important analytics workloads.\nWork with Vertica, SingleStore, Cloudera, and other strategic ecosystem partners to develop:\nEnable sales and presales organizations to identify, qualify, position, and architect analytics opportunities at scale.\nRequired Qualifications\n8+ years of experience in technical presales, solutions architecture, enterprise architecture, database architecture, or data engineering.\nStrong understanding of enterprise analytics and modern data architectures, including:Enterprise data warehouses\nAnalytical databases\nData lakes\nData Lakehouse’s\nDistributed data platforms\nObject storage\nETL/ELT pipelines\n\nExperience designing or supporting large-scale analytics environments.\nStrong understanding of analytical database characteristics, including:Data ingestion\nQuery processing\nConcurrency\nData distribution\nPartitioning\nPerformance\nCapacity scaling\n\nExperience with one or more enterprise analytics platforms such as:Vertica\nSingleStore\nCloudera\nTeradata\nOracle/Exadata\n\nDemonstrated ability to lead architecture discussions from data and workload requirements rather than starting with infrastructure.\nAbility to map end-to-end data flows across ingestion, transformation, storage, analytics, and consumption.\nExperience evaluating modernization strategies for traditional database or data warehouse environments.\nAbility to understand and evaluate performance requirements for large-scale analytical workloads.\nProven ability to lead customer discovery and translate business and technical requirements into solution architectures.\nStrong communication skills with the ability to engage both deeply technical and executive audiences.\nPreferred / Nice-to-Have Experience\nHands-on experience with Vertica, SingleStore, or Cloudera and familiarity to log analytics platforms such as Splunk and Elastic.\nExperience with Teradata or Oracle Exadata environments and modernization initiatives.\nExperience designing or migrating large enterprise data warehouses.\nFamiliarity with open data lake and Lakehouse technologies and architectures.\nFamiliarity with technologies such as Apache Iceberg and Spark, Trino, and modern data catalogs.\nExperience with cloud and hybrid analytics platforms.\nExperience developing TCO or business cases for database and data platform modernization.\nExperience working with Product Management, strategic ISVs, or influencing product strategy.\nWhat Success Looks Like\nEstablishing X10K as a strategic data platform for enterprise analytics rather than simply a storage target.\nCreating repeatable strategies for penetrating and displacing legacy architectures.\nBuilding strong joint solution motions around Vertica, SingleStore, Splunk, and Elastic.\nHelping customers successfully transition from traditional data warehouse architectures toward modern data lakehouse and open data architectures.\nPositioning solutions with precision-winning opportunities where the architecture provides meaningful technical and business advantages.\nEnabling field teams to confidently identify, qualify, size, and position analytics opportunities.\nInfluencing X10K product direction based on real-world analytics customer requirements.\nCreating repeatable reference architectures, sizing methodologies, migration patterns, and competitive plays that can be scaled globally.\nWhat We Can Offer You:\nHealth & Wellbeing\nWe strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their ph...","description_format":"text","description_chars":15505,"description_truncated":true,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["Professional development"],"hiring_locations":[{"name":"United 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