Senior Data Engineer

About the role

Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes.

Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively.

We are looking for a Senior Data Engineer to join a team migrating a production SaaS data platform off a legacy ETL/streaming-based pipeline and onto a Snowflake Native Application built for self-serve distribution and per-tenant data isolation.

This isn't a greenfield build — it's a migration with real legacy constraints. You'll be working from an existing production system that has already been audited in detail, and turning those findings into a working Snowflake-native data platform. You should be comfortable reading someone else's architecture, spotting where it breaks down at scale or under multi-tenant isolation requirements, and redesigning around it.

WHAT YOU'LL DO

- Re-architect ingestion — design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account so the platform's data-sovereignty story is true end to end.

- Migrate legacy ETL logic — translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines using the right combination of native transformation tooling and orchestration.

- Design for per-tenant isolation — build data models and pipeline logic that hold up under a cross-account, multi-tenant distribution model, with tenant boundaries addressed explicitly at the schema, pipeline, and secret-management level.

- Work through known technical debt — shared credentials baked into client-side builds, build-time-only configuration with no live tenant provisioning, inconsistent cross-platform data-capture parity — deciding case by case what gets carried forward, redesigned, or retired.

- Rebuild the platform's core data model — activity, event, network, and metadata — preserving the analytics the business depends on while moving underlying storage and processing into Snowflake.

- Validate against real production data patterns — batch sizes, sync frequencies, offline-queue backlogs — captured during discovery to ensure the new pipeline design holds up under realistic load.

- Document migration decisions clearly enough to be defended internally, to downstream customers, and through a formal marketplace review process.