Sr Data Engineer

THIS OPENING IS AVAILABLE FOR CANDIDATES IN LATIN AMERICA, NOT LIMITED TO ONLY MEXICO.

Sonatafy Technology, headquartered in Scottsdale, Arizona, is an award-winning nearshore software development company with a strong reputation. They have a dedicated in-house team of engineers, offering end-to-end software solutions and supporting client development staff augmentation. Catering to companies of all sizes and industries, including some of the world's largest brands, Sonatafy Technology is a trusted provider of nearshore enterprise-level cloud and mobile application software development services.

About the Role

We're looking for a senior analytics engineer with deep experience in dbt and Snowflake to join a Managed Delivery POD building a governed data platform for a multi-location franchise brand.

The platform is a layered Snowflake Enterprise instance (RAW, STAGING, CORE, MARTS, SANDBOX) fed by CDC, with functional RBAC and a dbt Cloud project. The role centers on the dbt transformation layer: staging models, identity resolution, Customer 360 core models, seven production marts, and the tests, contracts, and documentation that let the client's team own the platform after handoff.

You will work alongside the lead data architect and own a defined set of models end to end.

Key Responsibilities

Build and own dbt staging, intermediate, core, and mart models from ticket to production, following the project's naming, routing, and test conventions.

Turn business rules into documented, testable logic: survivorship, location attribution, consent history, membership lifecycle, and mart metrics.

Work directly with marketing, operations, and finance subject matter experts to confirm definitions, then get sign-off before a model is promoted.

Write tests and model contracts with every model. Add source freshness and soft-delete handling for CDC-landed tables.

Set up and maintain dbt Cloud Production and CI environments, and keep the main branch compiling and deployable.

Review pull requests from other engineers and take review from the lead architect.

Reconcile model output against source systems and write up any gap with its cause.

Document every attribute you build, and contribute to the runbooks and wiki pages used at

handoff.

Requirements

5+ years in data or analytics engineering, with at least 3 years building production dbt projects on Snowflake.

Strong dbt: layered modeling, incremental models, snapshots and SCD Type 2, macros and Jinja, packages such as dbt_utils, model contracts, exposures, and docs.

dbt testing in depth: generic and singular tests, source freshness, severity and failure handling, and CI that builds into isolated per-PR schemas.

Snowflake beyond querying: roles and grants, warehouses and cost controls, UDFs, Secure Views, masking policies, and tags.

Customer identity resolution or entity matching: deterministic match tiers, survivorship rules, and a stable customer key across source systems.

Expert SQL, including window functions and semi-structured data.

Experience handling PII and consent data with an append-only, auditable design.

Git-based workflow with pull requests, code review, and protected branches.

Clear written English and the habit of documenting decisions so others can pick up the work.

Nice to Have

dbt Cloud administration: environments, jobs, service users with key pair auth, and network policies.

Modeling data landed by CDC tools such as Snowflake OpenFlow or AWS DMS, including soft-delete flags.

Source familiarity with Zoho CRM, Customer.io, GA4 exports, or appointment and POS systems.

Multi-location or franchise reporting, including row-level security by franchise, market, or region.

Building marts for Power BI and matching metrics to existing report logic.

Consent and data deletion workflows across marketing and CRM tools.

Terraform or schema changes for Snowflake objects.

Why Work