Data Platform Analytics Architect

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Platform Analytics Architect based in the United States.

This is a strategic, customer-facing architecture role focused on modernizing enterprise analytics and data platforms at scale.

You will help organizations evolve from traditional data warehouses toward flexible, open, and scalable data lake and Lakehouse architectures.

The role combines deep expertise in data architecture, analytics workloads, databases, and modern infrastructure with strong customer engagement skills.

You will lead technical discovery, architecture design, sizing, modernization planning, and complex platform transformation discussions.

Working across customers, sales, engineering, product teams, and technology partners, you will shape repeatable solutions and go-to-market strategies.

Your work will directly influence how enterprise data is ingested, governed, stored, processed, queried, and consumed.

This is an opportunity to establish modern data platforms as strategic foundations for analytics while helping customers improve performance, scalability, flexibility, and economics.

Accountabilities

• Lead customer-facing architecture discussions centered on data, application, and analytics requirements, including data volumes, growth, ingestion, transformation, query patterns, retention, concurrency, performance, and real-time processing needs.
• Design modern analytics architectures that optimize ETL/ELT pipelines, compute-to-data access, query performance, data placement, scalability, interoperability, lifecycle management, reliability, and cost efficiency.
• Help customers transition from infrastructure-centric models toward data-centric architectures where multiple analytics engines and applications can leverage shared enterprise data assets.
• Assess traditional enterprise data warehouse environments and identify workloads and datasets that are strong candidates for modernization, migration, consolidation, or continued operation.
• Develop practical modernization strategies that move customers toward analytical databases, data lakes, and Lakehouse architectures while minimizing operational and technical risk.
• Build expertise across enterprise analytics platforms and ecosystems, including Vertica, SingleStore, Cloudera, Splunk, Elastic, and related technologies.
• Clearly articulate the architectural differences between traditional data warehouses, distributed databases, cloud-native databases, data lakes, and Lakehouse environments, recommending architectures based on workload requirements.
• Scope and size enterprise analytics environments using data volume, ingestion rates, retention, service-level requirements, performance expectations, and other customer-specific factors.
• Develop repeatable sizing methodologies, reference architectures, deployment patterns, migration approaches, and competitive strategies that can be leveraged by field and sales teams.
• Advise customers on open data and Lakehouse concepts including object storage, open data and table formats, schema evolution, metadata, cataloging, governance, data sharing, pipelines, distributed analytics, and compute/storage separation.
• Lead technical discovery sessions, translate business objectives into scalable architectures, and serve as a trusted advisor throughout complex data modernization initiatives.
• Identify opportunities for phased migrations, new workloads, data growth, archival use cases, and adjacent analytics initiatives that can provide practical entry points into legacy environments.
• Partner with Product Management, engineering, performance teams, ISVs, and strategic technology partners to validate workloads, influence product priorities, and address competitive gaps.
• Enable sales and presales teams to identify, qualify, position, size, and architect analytics opportunities consistently and effectively.
• Establish modern data platforms as strategic enterprise analytics foundations and create repeatable approaches that can scale across markets and customer environments.

Requirements

• 8+ years of experience in technical presales, solutions architecture, enterprise architecture, database architecture, data engineering, or a related technical discipline.
• Strong understanding of enterprise analytics and modern data architectures, including enterprise data warehouses, analytical databases, data lakes, Lakehouses, distributed data platforms, object storage, and ETL/ELT pipelines.
• Demonstrated experience designing or supporting large-scale analytics environments and understanding the technical behavior of analytical databases.
• Strong knowledge of data ingestion, query processing, concurrency, data distribution, partitioning, performance optimization, and capacity scaling.
• Experience with one or more enterprise analytics platforms such as Vertica, SingleStore, Cloudera, Teradata, or Oracle/Exadata.
• Ability to approach architecture from data and workload requirements rather than beginning with infrastructure considerations.
• Experience mapping end-to-end data flows across ingestion, transformation, storage, analytics, and consumption.
• Demonstrated ability to evaluate and develop modernization strategies for traditional database and data warehouse environments.
• Strong understanding of performance requirements for large-scale analytical workloads and the ability to establish realistic expectations across the complete analytics pipeline.
• Proven ability to lead customer discovery sessions and translate complex business and technical requirements into practical solution architectures.
• Excellent communication and presentation skills, with the ability to engage both highly technical stakeholders and executive audiences.
• Preferred experience with Vertica, SingleStore, Cloudera, Splunk, Elastic, Teradata, or Oracle Exadata.
• Familiarity with open data lake and Lakehouse technologies, including Apache Iceberg, Spark, Trino, modern data catalogs, and open table formats.
• Experience with cloud and hybrid analytics environments and enterprise data warehouse migration initiatives is preferred.
• Experience developing total-cost-of-ownership analyses or business cases for database and data platform modernization is a plus.
• Experience collaborating with Product Management, strategic ISVs, or technology partners and influencing product strategy is desirable.
• Strong commercial judgment and the ability to recognize where a proposed architecture provides meaningful technical and business value.
• Ability to work remotely while traveling to customer, temporary, or corporate locations as required.

Benefits

• Annual salary range of $161,000-$378,000 USD for the listed U.S. locations, including Illinois, Michigan, North Carolina, and Texas.
• Compensation reflects combined base salary and target-level sales compensation at 100% achievement of the applicable sales plan, with an 80% base / 20% target sales compensation mix.
• Remote/teleworker arrangement, with the primary work location being from home.
• Comprehensive benefits supporting physical, financial, and emotional well-being for employees and their families.
• Programs and resources dedicated to personal and professional development.
• Opportunities to build expertise, pursue career goals, and explore opportunities across different areas of the organization.
• An inclusive work environment that values diverse backgrounds, perspectives, and individual strengths.
• Flexibility designed to help employees manage professional and personal needs.
• Opportunity to work on innovative data, analytics, cloud, and enterprise technology initiatives with customers and strategic technology partners.
• Equal employment opportunities and reasonable accommodations for qualified individuals with disabilities.