Senior data engineer
Remoto LATAM
Esta vacante es 100% remota y está abierta a candidatos de cualquier país de LATAM (Argentina, Bolivia, Brasil, Chile, Colombia, México, Paraguay, Uruguay). Aunque la ficha menciona una ciudad, no es necesario residir allí: la empresa contrata desde toda la región.
OnHiresAmérica Latina (Remoto)
56 personas interesadas en esta vacante
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SalarioSalario no especificado
Jornadafull-time
Modalidadremote
Publicado15 sept
4+ años de experiencia
Acerca del puesto
Our client is a growing technology company developing market intelligence and software solutions. They are looking for a Senior Data Engineer to join a small international team and take ownership of complex data engineering challenges involving large-scale data processing, standardization, matching, and data quality.
Responsabilidades principales
Design, build, and maintain scalable production data pipelines. Ingest, process, and transform large volumes of data from multiple sources. Develop solutions for data standardization, normalization, matching, and validation. Build data quality controls and monitoring to identify malformed, inconsistent, or incorrect data. Design reliable approaches to data corrections, updates, reprocessing, and backfills. Improve the architecture, scalability, reliability, and performance of the data platform. Take end-to-end ownership of technical solutions and production quality. Work closely with a small engineering team while independently driving your area of responsibility. Use AI-assisted engineering tools and practices to improve development efficiency.
Beneficios
- 100% remote work from LATAM
- Full-time B2B contract
- High level of technical ownership and autonomy
- Direct impact on architecture and product development
- Complex engineering challenges rather than narrowly defined implementation tasks
- Small, international team with direct communication and minimal bureaucracy
- Professional development and continuous learning opportunities
Condiciones laborales
4+ years of hands-on Data Engineering experience with production data systems. Strong Python skills. Hands-on experience with PySpark / Apache Spark and distributed data processing. Strong experience building and maintaining ETL/ELT and data ingestion pipelines. Experience working with large, complex datasets and multiple data sources. Strong SQL and data modeling skills. Experience with modern data platforms, data lakes, lakehouse, or similar architectures. Strong understanding of data quality, validation, monitoring, and data reliability. Ability to independently design solutions, troubleshoot production problems, and take ownership of delivery. Fluent English.
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