Magnet Forensics

Data Architect (Distributed Systems Engineering)

Job Description

Role Overview

We're seeking an exceptional Data Architect to lead data storage strategy and design across our multi-product SaaS platform as we unify independent products into a coherent platform. This role combines strategic leadership with hands-on technical expertise—you'll shape our data architecture vision while getting into the details during implementation and troubleshooting.
 
NOTE: Candidate must reside in The United States.


Key Responsibilities
  • Drive data architecture unification across multiple SaaS products, creating coherent patterns while respecting product needs.
  • Partner with vertical technical leads to provide horizontal architectural support and alignment.
  • Design and optimize data storage across multiple technologies—AWS OpenSearch/Elasticsearch, relational databases, S3, NoSQL, and data warehousing.
  • Optimize for performance and resilience— indexing, querying, high availability, redundancy, and disaster recovery at scale.
  • Support AI initiatives—partner with our AI specialist team on data architecture for AI capabilities.
  • Bring clarity from ambiguity—translate complex challenges into clear architectural direction.
  • Build capability, not dependencies—mentor engineers so teams become more self-sufficient.
  • Balance performance, cost, and reliability across our platform.

    • Qualifications
  • Deep expertise in AWS OpenSearch/Elasticsearch—you've solved hard problems at scale with indexing, querying, and performance.
  • Broad data technology experience—relational databases (e.g. PostgreSQL, MySQL, RDS), object storage (S3), NoSQL (e.g. DynamoDB, MongoDB, Redis), data warehousing.
  • Cloud and container knowledge—AWS preferred (Azure/GCP also valued); understand stateful services in Kubernetes.
  • Proven platform architecture experience—track record of driving technical strategy across multiple teams or products at scale.
  • Senior-level maturity—you make those around you better through mentorship and capability building.
  • Influence without authority—you work effectively across teams, bring clarity from ambiguity, and think strategically.
  • SaaS experience—comfortable with multi-tenant environments and operational excellence.

    • What Success Looks Like in Year 1
  • Data alignment strategy executed—platform stores and searches data more efficiently.
  • 2-3 high-impact problems resolved—key blockers addressed with measurable reliability improvements.
  • Teams operating independently—engineers understand the "why" and apply principles without needing you for every decision.
  • Knowledge multiplying—people you've mentored are teaching others.
  • Working at high leverage—guiding multiple teams, not embedded in any single one.

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