Data Architect

The CHI Software team is not standing still. We love our job and give it one hundred percent of us! Every new project is a challenge that we face successfully. The only thing that can stop us is… Wait, it’s nothing! The number of projects is growing, and with them, our team too. And now we need a Data Architect.

About Our Customer

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.

Requirements

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.

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.