Senior BI/Data Engineer: Power BI, SQL, Snowflake — Remote

Agileengine, Llc.; Ciudad de Mendoza; Hybrid; ARS 139,312,000 - 201,229,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine is seeking a Mid-level Data Engineer to build and maintain dbt pipelines and Snowflake data marts behind customer-facing reporting, spend analytics, and AI features.

The role requires solid dbt experience, ingestion/orchestration tools (Airbyte, Prefect), 3+ years in data/analytics engineering on production pipelines, strong SQL and Python, and upper-intermediate English. You will work across data, engineering, and product teams.

Qualifications

• 3+ years in analytics engineering or data engineering with production pipelines.
• Solid dbt experience: modeling, tests, macros, and incremental models.
• Strong SQL and Python.
• Data modeling fundamentals: dimensional modeling, data marts, grain and conformance.
• Experience with a modern cloud warehouse (Snowflake preferred).
• Experience with ingestion tooling and orchestration (Airbyte, Prefect, or equivalents).
• Familiarity with agentic coding tools and guardrails around their output.
• Curiosity about the business and how data is used by customers.
• Software engineering discipline for analytics code: Git, code review, CI/CD.
• Ability to take a multi-sprint piece of work from spec to production.

Responsibilities

• Build and maintain the dbt pipelines, data marts, and warehouse models for reporting, spend analytics, and AI features.
• Translate procurement business logic into maintainable pipeline code with tests.
• Build models within data mart architecture following grain and conformed dimensions.
• Contribute to semantic layer definitions for MCP servers and AI agents.
• Maintain boundary between PII and reporting-safe data.
• Build and maintain FastAPI services exposing reporting marts to customers.
• Ingest data into the warehouse using Airbyte, OneSchema, and S3; support Forward Deployed Engineering.
• Implement data quality checks: freshness, schema checks, reconciliation tests, alerts.
• Define metric definitions faithfully and flag conflicting definitions.
• Keep documentation and data lineage current for humans and AI.
• Tune Snowflake performance and cost; optimize warehouse models.
• Use agentic coding tools within guardrails; share learnings via code reviews.
• Communicate data meanings to engineering, product, and customer teams.

Skills

Analytics engineering

Data engineering

Production pipelines

Tools

dbt

Airbyte

Prefect

Snowflake

Python

SQL

Job description

AgileEngine is seeking a Mid-level Data Engineer to build and maintain dbt pipelines and Snowflake data marts behind customer-facing reporting, spend analytics, and AI features.

The role requires solid dbt experience, ingestion/orchestration tools (Airbyte, Prefect), 3+ years in data/analytics engineering on production pipelines, strong SQL and Python, and upper-intermediate English. You will work across data, engineering, and product teams.