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Nagarro

Staff Engineer - Data Engineer

Nagarro Guadalajara, Sonora, Mexico

IT Services and IT Consulting · 10,001+ employees

Sep 07
data-engineer Senior (5-10 yrs) Full-time Mexico
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About the role

Develop complex data transformations and manage data pipelines using dbt. Ensure data quality and maintain documentation and lineage for data models.

What they look for

Data Engineering Analytics Engineering Dbt SQL Data Transformation Dbt Core Dbt Cloud Incremental Models Jinja Data Quality Frameworks Snowflake Databricks BigQuery Amazon Redshift Data Lineage

Requirements

Requires 6+ years of experience in data engineering and 3+ years of hands-on experience with dbt in production. Strong proficiency in SQL and experience with cloud data platforms like Snowflake or Databricks is essential.

Full description

Company Description

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale — across all devices and digital mediums, and our people exist everywhere in the world (15000+ experts across 26 countries, to be exact). Our work culture is dynamic and non-hierarchical. We are looking for great new colleagues. That is where you come in!

Job Description

  • 6+ years of experience in Data Engineering, Analytics Engineering, or related fields.
  • 3+ years of hands-on experience with dbt in production environments.
  • Strong expertise in SQL and complex data transformation development.
  • Strong understanding of dbt Core and/or dbt Cloud.
  • Experience with dbt, including• dbt models and materialization
  • Incremental models
  • Macros and Jinja
  • dbt tests and data quality frameworks
  • Snapshots
  • Seeds and sources
  • Documentation and lineage
  • dbt packages
  • Strong experience with at least one cloud data platform, such as:•  Snowflake
  • Databricks
  • BigQuery
  • Amazon Redshif

​​​​​​​AI skills (required for all roles)

  • Daily, fluent use of Claude Code and/or GitHub Copilot for implementation, refactoring, test generation, and code review
  • Ability to establish team standards for AI-assisted development: effective prompting, trust-vs-verify discipline on generated code, security/IP guardrails, and reviewing AI-authored changes
  • Working understanding of LLM fundamentals: context windows, tokens, model selection, and prompt/context engineering
  • Experience integrating AI into developer workflows and agentic/automation tooling (MCP servers, AI-driven CI steps, codegen and doc-generation pipelines)
  • Able to evaluate AI tooling pragmatically: measuring real productivity and quality impact, not hype

 

  • Service Region: UCC

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