Data Engineer - Data Foundry Engineer

🕒 Abril 2

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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

• Design and maintain robust data pipelines to ingest from a wide range of sources, including APIs, documents, websites, and raw sensor data • Integrate and optimize ETL/ELT processes developed by MLE colleagues, improving performance, reliability, and long-term maintainability • Own the full dataset lifecycle, from raw ingestion through cleaning, validation, and delivery as training-ready data • Define and enforce data quality standards and governance practices across the Data Foundry team • Build and maintain labeling pipeline infrastructure for ML applications, working closely with the annotation team • Participate in architectural decisions, code reviews, and technical mentorship within the team • Document data sources, pipeline logic, and processing decisions for reproducibility and team alignment

🎯 Requisitos

• 3+ years of experience in data engineering • Degree in Computer Science, Data Engineering, Computer Engineering, Information Systems, or equivalent technical background • Solid understanding of the ML training lifecycle and what properties make a dataset suitable for model training • Familiarity with layered data architecture patterns such as Medallion Architecture (Bronze/Silver/Gold) or Data Mesh • Proficiency in Python, with focus on data manipulation, pipeline development, and automation • Workflow orchestration using code-based tools such as Temporal, Airflow, Prefect, Dagster, or equivalent • Distributed data processing with Spark, Databricks, or similar • REST and gRPC API integration • Strong SQL skills, both for data modeling and query optimization • Experience with streaming systems and event-driven pipelines (Kafka, Kinesis, or equivalent)