Magnetforensics2mo ago

Data Architect (Distributed Systems Engineering)

United StatesRemoteFull-Timemid

Data ArchitectData & AI

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Quick Summary

Overview

Who We Are; What We Do; Where We’re Going Magnet Forensics is a global leader in the development of digital investigative software that acquires, analyzes, and shares evidence from computers, smartphones, tablets, and IoT-related devices.

Technical Tools

awsazuredynamodbelasticsearchgcpkubernetesmongodbmysqlpostgresqlredisdistributed-systemsmentoringsaas

Who We Are; What We Do; Where We’re Going

Magnet Forensics is a global leader in the development of digital investigative software that acquires, analyzes, and shares evidence from computers, smartphones, tablets, and IoT-related devices. We are continually innovating so our customers can deploy advanced and effective tools to protect their companies, communities, and countries.

Serving thousands of customers globally, our solutions are playing a crucial role in modernizing digital investigations, helping investigators fight crime, protect assets, and guard national security.

With employees based around the world, Magnet Forensics has been expanding our global presence. As a part of Magnet Forensics, you can expect to make a difference in the world, no matter what role you play. You’ll be supported through learning and development, not to mention an incredible team with unbelievable talent and integrity.

If you think you would be the right person to join our team working towards this goal, we would love to hear from you!

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.

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.

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.

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.