Staff Engineer - Data Engineer

Nagarro • English • SQL • 8 hours ago
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Location
Remote/Hybrid (Guadalajara, Mexico)
Seniority
Staff · 6+ years exp
Employment
Full-Time
Overview
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Nagarro

Nagarro is a digital engineering company founded in 1996 and headquartered in Munich, which spun out of the Allgeier group and listed on the Frankfurt exchange in 2020. It builds custom software, cloud platforms and automation for clients across automotive, retail, financial services, travel and manufacturing, delivered by a globally distributed workforce concentrated in India, Eastern Europe and Latin America. The company describes its structure as deliberately non-hierarchical and fluid, and it has grown largely through a steady run of acquisitions that add regional presence and specialist practices rather than through a single large merger.
nagarro.com • HQ: Munich, Germany • IT Outsourcing • Custom Software Development • Cloud Computing • IT Consulting • 5000+ employees • Est. 1996

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!

  • 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 Redshift
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