Lead Data Engineer

Niuro

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La fuente no informa: contrato, experiencia, sueldo, cierre.

Resumen

Own the end-to-end data platform: architecture, pipelines, quality, and governance.
Develop a deep understanding of the business and how its data is generated, and translate that into architecture and design decisions.
Drive the remediation and optimization of existing data assets, ensuring quality, consistency, and reliability across core datasets.
Design, build, and operate reliable data pipelines between SQL Server, BigQuery, and third-party integrations.
Define and implement the target data architecture, including layered modeling (medallion), data cataloging, and lineage.

5+ years of experience designing and operating production data pipelines at scale, ideally within fintech or lending environments
Proven ability to quickly understand a business domain and how its data is generated, and translate that into architecture decisions
Demonstrated experience inheriting legacy data structures and remediating them end-to-end — data cleanup, deduplication, and quality frameworks
Strong proficiency in Google Cloud (BigQuery) and working knowledge of Azure (Data Factory, ADLS)
Production-level Python and strong SQL fluency, including BigQuery-specific optimization patterns like partitioning, clustering, and cost control
Experience implementing medallion architecture with explicit schema contracts and lineage between layers
Experience mentoring engineers or leading small teams is a plus
Hands-on by default — you build, not just direct
Fluent spoken Spanish

Skills

Última verificación en WIAK: 4 nov. Revisa siempre la vigencia en la fuente.