Senior Principal Solutions Architect

The Senior Principal Solutions Architect – Vertica is a highly experienced technical leader responsible for driving adoption of Rocket Software’s Vertica analytics platform across complex, data‑intensive enterprise environments. This role drives customer engagement, proof‑of‑concept leadership, and technical sales execution while shaping internal strategy for high‑performance analytical solutions.

Key Responsibilities

• Strategic Customer Engagement & Solution Design
  • Act as a trusted technical advisor to enterprise customers, translating business challenges into scalable Vertica‑based analytical architectures.
  • Lead discussions across data warehousing, data lake analytics, and hybrid/multi‑cloud environments.
  • Influence customer data platform and modernization strategies, positioning Vertica as the core analytical engine.
  • Engage effectively with stakeholders ranging from hands‑on engineers to senior executives.
• Proof of Concept & Benchmark Leadership
  • Own the end‑to‑end design and execution of competitive proof‑of‑concepts (POCs) and performance benchmarks under tight sales timelines.
  • Translate technical outcomes (query performance, compression, concurrency) into compelling business value (cost reduction, speed, ROI).
  • Design realistic data models, workloads, and benchmarking frameworks aligned to customer use cases.
  • Clearly differentiate Vertica from alternative MPP and cloud data warehouse solutions.
• Technical Sales Leadership
  • Lead the technical strategy for new business, expansion, and strategic opportunities.
  • Partner closely with Sales to develop account strategies, deal plans, and winning technical narratives.
  • Guide and mentor Sales Engineers, ensuring high‑quality demos and solution validation.
  • Drive complex, multi‑stakeholder technical sales cycles from discovery through close.
• Data Architecture & Modern Data Stack Integration
  • Design solutions integrating Vertica across modern ecosystems, including ingestion (Kafka, Spark, streaming pipelines), storage (S3, HDFS, object storage), and consumption (Tableau, Power BI, Looker, and other BI platforms).
  • Provide guidance on data modelling and schema design, data governance, quality, and cleansing practices, and ETL/ELT pipeline architecture and performance optimisation.
• Hands‑on Technical Execution
  • Write and optimise complex analytical SQL queries on large‑scale datasets.
  • Develop scripts (Python, shell) to support automation, data loading, and demo environments.
  • Deploy and configure Vertica environments across on‑premises, hybrid, and cloud platforms.
  • Troubleshoot performance issues and optimise query execution in real‑time scenarios.
• Ecosystem & Partner Collaboration
  • Work closely with cloud providers (AWS, Azure, GCP), GSIs, VARs, and ISVs to deliver joint solutions.
  • Support co‑sell opportunities and align on shared value propositions.
  • Contribute to partner enablement and field readiness.
• Thought Leadership & Organisational Impact
  • Define and promote best practices, architectural patterns, and reusable assets across the Solutions Architecture community.
  • Influence technical sales strategy, including POC methodologies and competitive positioning frameworks.
  • Mentor and coach other Solutions Architects and Sales Engineers.
  • Act as a technical thought leader, representing Rocket in key customer and industry engagements.
  • Contribute to innovation in areas such as AI/ML integration, advanced analytics, and emerging data architectures.

Experience and Qualifications

• Core Experience
  • 10+ years of experience in solutions architecture, presales, or technical consulting roles.
  • Minimum 3–5 years in a customer‑facing presales role, preferably in Data Warehouse or Data Lake analytics.
  • Proven experience with columnar, MPP, or OLAP databases, such as Vertica, Teradata, Greenplum, ClickHouse, or equivalent.
• Technical Expertise
  • Strong proficiency in ANSI SQL and major SQL dialects (PL/SQL, T‑SQL, etc.), query optimisation and performance tuning, data modelling and warehouse design (star/snowflake schemas), ETL/ELT pipeline development and orchestration, and data governance, data quality, and data cleansing practices.
  • Experience working with streaming and ingestion frameworks: Kafka, Spark; data lake and storage platforms: S3, HDFS; and BI and visualisation tools: Tableau, Looker, Power BI.