Remote Data Engineer: dbt, Snowflake & AI Analytics

Bairesdev; Ciudad de Mendoza; Hybrid; ARS 139,086,000 - 200,903,000; Full time

Benefits offered by this job

Professional growth

USD-based pay

Remote and office options

TechTalks and growth roadmaps

Job summary

BairesDev is seeking a mid-level Data Engineer to design, build, and maintain dbt pipelines and Snowflake data marts powering customer reporting and analytics. You will own production-grade data models and contribute to AI-ready data layers.

You will collaborate with product and engineering teams, implement data quality checks, and build FastAPI services to expose reporting marts. A flexible hybrid/remote setup is available.

Qualifications

• 3+ years in analytics engineering or data engineering with production pipelines.
• Strong SQL and Python skills with production-grade code.
• Solid dbt experience for modeling, tests, macros, and incremental models.
• Experience with Snowflake or a modern cloud data warehouse.
• Familiarity with data quality checks and data governance concepts.
• Experience building API services on top of data warehouses is a plus.
• Upper-intermediate English level.

Responsibilities

• Build and maintain the dbt pipelines, data marts, and warehouse models that serve in-app reporting, spend analytics, AI features, and internal analytics, treating them as production systems.
• Translate complicated procurement business logic into maintainable, well‑tested pipeline code, and notice when a model is valid‑looking but wrong.
• Build models within our data mart architecture, following grain, conformed dimensions, and incremental patterns, and propose improvements when you find them.
• Contribute to and help buildout the semantic layer that our internal MCP servers and AI agents query, so that metrics and dimensions are defined once and answered consistently.
• Maintain the boundary between PII and agent/reporting‑safe data.
• Build and maintain ingestion pipelines (Airbyte, OneSchema, S3) into the warehouse, and support Forward Deployed Engineering in bringing customer data into our systems.
• Implement data quality checks: freshness, schema and reconciliation tests, and alerting, so problems surface before customers find them.
• Implement metric definitions faithfully, and flag conflicting or ambiguous definitions to the chapter rather than guessing.
• Keep documentation and lineage current so that humans and AI agents can both find and trust what's in the warehouse.
• Tune Snowflake performance and cost within the models you build.
• Use agentic coding tools in your daily work, within the guardrails the team maintains, and understand why those guardrails exist.
• Share what you learn through code review and team discussion.
• Communicate clearly with engineering, product, and customer‑facing teams about what the data means and what it can and can't do.

Skills

SQL

Python

dbt

Data modeling

Git & CI/CD

Analytics engineering

Communication

English

Tools

Snowflake

Airbyte

OneSchema

S3

FastAPI

Prefect

Job description

BairesDev is seeking a mid-level Data Engineer to design, build, and maintain dbt pipelines and Snowflake data marts powering customer reporting and analytics. You will own production-grade data models and contribute to AI-ready data layers.

You will collaborate with product and engineering teams, implement data quality checks, and build FastAPI services to expose reporting marts. A flexible hybrid/remote setup is available.