Senior Data Engineer

🕒 Janeiro 8

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TRACTIAN

SiteLinkedInTodas as Vagas

51 - 200 funcionários

🏢 Corporativo

⚡ Energia

Enterprise • Industrial • Energy

TRACTIAN é uma empresa especializada em Asset Performance Management (APM), oferecendo soluções líderes de mercado para garantir zero downtime em plantas industriais. Com produtos como Smart Trac Condition Monitoring & Auto Diagnosis e TracOS™ Maintenance Management Software, a TRACTIAN permite que gestores de plantas prevejam falhas, evitem paradas e gerenciem ativos com eficiência. Suas soluções também focam em eficiência energética, transformando dados de consumo de energia em lucro. A TRACTIAN colabora com setores como automotivo, mineração, óleo e gás e farmacêutico, oferecendo insights avançados e diagnósticos com IA para aumentar a confiabilidade das máquinas e a eficiência operacional.

Descrição

• Develop and maintain scalable data pipelines and ETL processes. • Design, implement, and optimize existing data extraction and loading processes with adequate data engineering design patterns. • Lead data engineering reliability and observability, increasing analytics team awareness of the data flow processes before it becomes an issue. • Collaborate with backend and analytics engineers in a holistic data engineering process, loading data accordingly with the technical requirements. • Ensure data quality and consistency across various sources by implementing data validation and cleansing techniques. • Work with cloud-based data warehouses and analytics platforms to manage and store large datasets. • Monitor and troubleshoot data pipelines to ensure reliable and timely delivery of data. • Document data processes, workflows, and best practices to enhance team knowledge and efficiency. • Create dashboards as data products as internal

🎯 Requisitos

• Bachelor degree in Data Science, Statistics, Computer Science, or a related field. • Advanced English • 2+ years of experience in Data Engineering or Analytics. • Highly experienced in SQL and database management systems such as PostgreSQL and Clickhouse . • Strong understanding of data warehousing concepts and experience with ETL tools (e.g., Airflow, dbt). • Strong experience with programming languages such as Python with modern data stack for data engineering (e.g. DuckDb, Polars...) • Experience with streaming tools (e.g. Kafka). • Experience with cloud-based data platforms like AWS Redshift. • Experience with GoLang/Rust is a plus. • Experience with observability tools is a plus (e.g. Datadog, Grafana)