Senior Data Engineer

🕒 January 8

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TRACTIAN

WebsiteLinkedInAll Job Openings

51 - 200 employees

🏢 Enterprise

⚡ Energy

Enterprise • Industrial • Energy

TRACTIAN is a company specializing in Asset Performance Management, providing industry-leading solutions to ensure zero downtime for manufacturing plants. With products like Smart Trac Condition Monitoring & Auto Diagnosis and TracOS™ Maintenance Management Software, TRACTIAN enables plant managers to predict failures, avoid downtime, and manage assets efficiently. Their solutions also focus on energy efficiency, transforming energy consumption data into profit. TRACTIAN collaborates with industries such as automotive, mining, oil and gas, and pharmaceuticals, offering advanced insights and AI-powered diagnostics to enhance machine reliability and operational efficiency.

📋 Description

• 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

🎯 Requirements

• 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)