Associate Staff Engineer - Data Engineer

Posted 9 Days Ago
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Hiring Remotely in Guadalajara, Jalisco, MEX
Remote or Hybrid
Mid level
Artificial Intelligence • Information Technology • Machine Learning • Software • Virtual Reality • Analytics
The Role
Design and maintain scalable Snowflake data models, dbt projects, and ELT/ETL pipelines. Optimize Snowflake performance and costs, develop Python-based workflows, and integrate data from ERP, MES, IoT, APIs, and files. Implement data quality, governance, lineage, testing, documentation, and CI/CD practices. Support analytics and reporting through optimized datasets and BI tools such as Power BI and Tableau.
Summary Generated by Built In
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

Role and Responsibility:

  • Design & Build Data Models: Architect and develop scalable, performant data models in Snowflake using dimensional modeling (star/snowflake schemas), OBT, and Data Vault patterns. You''''ll own the data warehouse layer that powers analytics and reporting across the organization.
  • Develop & Maintain dbt Projects: Build, test, and document dbt models end-to-end — staging, intermediate, and mart layers. Enforce best practices including version control, CI/CD, data contracts, and comprehensive testing (schema, data, and freshness tests).
  • Snowflake Cost Optimization: Monitor and optimize Snowflake compute and storage costs. This includes warehouse sizing and auto-suspend tuning, query profiling, clustering key strategies, materialization choices, and implementing resource monitors to control spend.
  • Data Pipeline Development: Design and build robust ELT/ETL data pipelines to ingest, transform, and deliver data from diverse sources (ERP, MES, IoT, APIs, flat files) into Snowflake/ AWS Glue/ Lambda. Automate workflows using orchestration tools and Python scripting.
  • Data Quality & Governance: Implement data quality checks, lineage tracking, and documentation standards. Champion data governance practices to ensure trusted, reliable data across the organization.

Expectation from the Candidate:

  • Experience: 3+ years of experience in data engineering, analytics engineering, or a related role, with hands-on Snowflake and dbt experience in a production environment.
  • Technical Prowess:
    • Expert-level Snowflake skills: data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams/tasks, data sharing, and cost management.
    • Strong dbt proficiency: model development, Jinja/macros, packages, incremental models, snapshots, exposures, and CI/CD integration.
    • Advanced SQL skills for complex transformations, window functions, CTEs, and analytical queries.
    • Proficiency in Python for data pipeline development, automation, scripting, and API integrations.
    • Experience with dashboard/BI tools (Power BI, Tableau) including data source optimization and DAX/LOD calculations.
    • Cloud platform experience (Azure, AWS, or GCP) including storage, compute, networking, and infrastructure-as-code basics.

Qualifications

Must have skills: Cloud development (Strong), DBT, SQL (Expert), Snowflake

Skills Required

  • 3+ years of experience in data engineering, analytics engineering, or a related role
  • Hands-on production experience with Snowflake and dbt
  • Strong cloud development experience
  • Expert SQL skills
  • Snowflake experience
  • Expert-level Snowflake skills, including data modeling, performance tuning, query optimization, Snowpark, stored procedures, streams and tasks, data sharing, and cost management
  • Strong dbt proficiency, including models, Jinja, macros, packages, incremental models, snapshots, exposures, and CI/CD integration
  • Advanced SQL skills involving complex transformations, window functions, CTEs, and analytical queries
  • Python proficiency for pipeline development, automation, scripting, and API integrations
  • Experience with Power BI or Tableau, including data source optimization and DAX or LOD calculations
  • Cloud platform experience with Azure, AWS, or GCP, including storage, compute, networking, and infrastructure-as-code basics

Nagarro Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Nagarro and has not been reviewed or approved by Nagarro.

  • Pay Growth & Progression — Compensation is at times described as competitive, with salary hikes and perks occurring on certain occasions. Better growth opportunities and compensation are also positioned as an advantage versus other service-based companies.
  • Flexible Benefits — Work arrangements are framed around a “work-from-anywhere” mindset with flexitime and family-friendly working models. This flexibility appears to add meaningful value to the overall rewards package for many roles.
  • Healthcare Strength — Medical, dental, and vision coverage are described as available for employees and dependents, alongside life insurance. Mental-health support is also included via an Employee Assistance Program (EAP).

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The Company
HQ: Munich
19,994 Employees
Year Founded: 1996

What We Do

Nagarro helps future-proof your business through a forward-thinking, fluidic, and CARING mindset. We excel at digital engineering and help our clients become human-centric, digital-first organizations, augmenting their ability to be responsive, efficient, intimate, creative, and sustainable. Today, we are 19,000 experts across 36 countries, forming a Nation of Nagarrians, ready to help our customers succeed.

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