Data Platform Analytics Architect

Quick Facts

• Remote/Teleworker

Description

A strategic, technically grounded Data Platform Analytics Solutions Architect role focused on driving growth for an enterprise analytics data platform. You will lead data-first architecture discussions on how data is ingested, stored, processed, queried, governed, and consumed across modern analytics environments, helping customers modernize traditional warehouses into scalable data lake and Lakehouse architectures.

Responsibilities

• Lead data-centric analytics architecture discussions covering volumes/growth/velocity, data types, ingestion and transformation, query patterns, data locality/movement/duplication, retention/lifecycle, and batch/streaming/real-time requirements
• Design modern analytics architectures to optimize ingestion/ETL-ELT pipelines, compute-to-data access patterns, query performance and concurrency, placement and movement, scalability, interoperability, and cost efficiency
• Assess traditional enterprise data warehouse environments and develop recommendations and phased modernization strategies (including which workloads to migrate/modernize/consolidate/retain)
• Develop deep expertise in analytics and data platforms aligned to X10K, including Vertica, SingleStore, and Cloudera, and also search/observability and machine-data analytics platforms (e.g., Splunk, Elastic)
• Scope and size analytics environments based on data volumes, ingest rate, retention, SLAs, and pipeline behavior; establish performance expectations from ingestion through transformation, query processing, and data protection
• Create migration and modernization approaches that avoid unnecessary “big bang” migrations and reduce technical/operational risk
• Run customer discovery sessions and translate business objectives into scalable analytics and data platform architectures for technical and executive audiences
• Partner with Product Management, engineering/performance teams, ISVs, and solution teams to validate workloads and deliver repeatable reference architectures, sizing methodologies, and go-to-market motions
• Position X10K as an enterprise data foundation within broader enterprise data architecture, emphasizing benefits of separating compute from data

Benefits

• Health & Wellbeing benefits
• Personal & Professional Development programs
• Unconditional Inclusion and flexibility to manage work and personal needs