Solution Engineer Quantexa

• Support technical discovery with business, data, and engineering stakeholders to understand objectives, data landscape, and success criteria for Quantexa use cases; capture outcomes and inputs for solution design.
• Contribute to solution architecture and implementation design on the Quantexa platform (data ingestion, entity resolution, network generation, analytics, and integration patterns) by drafting options, documenting decisions, and supporting reviews.
• Build and deliver platform demonstrations, prototypes, and proof-of-concepts, including data modeling, pipeline configuration, and analytic outputs to showcase value.
• Support integration with enterprise systems (data sources, APIs, messaging, identity, and security) by helping define interface requirements, validating assumptions, and assisting with performance, scalability, and resilience analysis.
• Partner with the Technical Lead (VP) and implementation teams to translate solution designs into delivery epics/stories; support delivery execution and help unblock teams through hands-on troubleshooting.
• Support release readiness by validating environments, deployment approaches, and operational runbooks; assist with production issue triage and coordination as needed.
• Create technical documentation (architecture diagrams, configuration notes, data mappings, and admin guidance) and enablement materials.
• Stay current on Quantexa features, accelerators, and best practices; share learnings and contribute reusable assets (demo datasets, templates, reference architectures).

• Bachelor’s or master’s degree in computer science, Information Technology, Data Science, or a related field (or equivalent practical experience).
• 5+ years of experience in solution engineering, technical consulting, or implementation roles delivering data/analytics platforms.
• Hands-on experience with the Quantexa platform (configuration, data pipelines, entity resolution, network analytics) and the ability to explain technical concepts to non-technical audiences.
• Strong understanding of data integration patterns (batch/streaming), ETL/ELT concepts, APIs, and data quality/lineage practices.
• Proficiency with modern engineering tools and delivery practices (e.g., Git, CI/CD pipelines, artifact repositories) and comfort working in agile delivery models.
• Experience with big data and distributed processing concepts (e.g., Spark) and familiarity with Scala and/or Python.
• Experience working on cloud computing platforms (Azure preferred).
• Excellent written and verbal communication skills, with proven ability to support workshops, communicate technical concepts clearly, influence stakeholders, and drive closure on action items.

• Experience in financial crime, fraud, AML transaction monitoring, or customer intelligence use cases.
• Experience designing entity resolution and graph/network analytics solutions, including tuning and evaluation approaches.
• Exposure to MLOps/ModelOps, feature engineering, and model integration patterns in production environments.
• Certification in Quantexa or related data analytics technologies is a plus.

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