[Hiring] Data Platform Analytics Architect @Hewlett Packard Enterprise

Role Description

We 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.

The 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.

A 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.

You 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.

A 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.

This 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.

Qualifications

• 8+ years of experience in technical presales, solutions architecture, enterprise architecture, database architecture, or data engineering.
• Strong understanding of enterprise analytics and modern data architectures, including:
  • Enterprise data warehouses
  • Analytical databases
  • Data lakes
  • Data Lakehouse’s
  • Distributed data platforms
  • Object storage
  • ETL/ELT pipelines
• Experience designing or supporting large-scale analytics environments.
• Strong understanding of analytical database characteristics, including:
  • Data ingestion
  • Query processing
  • Concurrency
  • Data distribution
  • Partitioning
  • Performance
  • Capacity scaling
• Experience with one or more enterprise analytics platforms such as:
  • Vertica
  • SingleStore
  • Cloudera
  • Teradata
  • Oracle/Exadata
• Demonstrated ability to lead architecture discussions from data and workload requirements rather than starting with infrastructure.
• Ability to map end-to-end data flows across ingestion, transformation, storage, analytics, and consumption.
• Experience evaluating modernization strategies for traditional database or data warehouse environments.
• Ability to understand and evaluate performance requirements for large-scale analytical workloads.
• Proven ability to lead customer discovery and translate business and technical requirements into solution architectures.
• Strong communication skills with the ability to engage both deeply technical and executive audiences.

Requirements

• Lead architecture discussions starting with the customer's data, applications, and analytics requirements, including:
  • Data volumes, growth rates, velocity, and distribution
  • Structured, semi-structured, and unstructured data
  • Data ingestion and transformation requirements
  • Query patterns and analytical processing requirements
  • Data locality, gravity, movement, and duplication
  • Data retention and lifecycle requirements
  • Batch, streaming, and real-time analytics requirements
  • Concurrency and performance expectations
• Design modern analytics architectures by optimizing:
  • Data ingestion and ETL/ELT pipelines
  • Compute-to-data access patterns
  • Query performance and concurrency
  • Data placement and movement
  • Storage and compute scalability
  • Open data access and interoperability
  • Data lifecycle and retention
  • Performance, reliability, and cost efficiency
• Help customers evolve from infrastructure-centric architectures toward data-centric architectures.
• Lead technical assessments of traditional enterprise data warehouse environments.
• Develop modernization strategies that transition customers from traditional data warehouses toward modern analytical databases and data Lakehouse architectures.
• Develop deep expertise in analytics and data platforms strategically aligned to X10K.
• Scope and size enterprise analytics environments based on data volumes, size, ingest rate, retention, SLA, and other customer specific functional requirements.
• Help customers design and adopt modern data lake and data Lakehouse architectures.
• Lead technical discovery sessions with enterprise customers to identify, shape, and qualify analytics modernization opportunities.

Benefits

• Health & Wellbeing: Comprehensive suite of benefits that supports physical, financial, and emotional wellbeing.
• Personal & Professional Development: Specific programs catered to helping you reach any career goals you have.
• Unconditional Inclusion: A culture that celebrates individual uniqueness and values varied backgrounds.