Mid-Level Data Engineer

Job not on LinkedIn

🕒 July 30

🇧🇷 Brazil – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🚰 Data Engineer

👻 Ghost score 29%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Sonepar

WebsiteLinkedInAll Job Openings

10,000+ employees

🤝 B2B

📦 Logistics

B2B • Logistics

Sonepar is a global distributor of electrical products and related services. According to its careers site, Sonepar comprises 90 leading brands operating in 40 countries and offers broad international career opportunities; it emphasizes distribution of electrical supplies through many local brands and a global network. The company focuses on serving professional customers through wholesale/distribution channels and supporting an extensive supply chain and logistics operation.

📋 Description

• Build and enhance scalable data pipelines. • Develop processes for data ingestion, transformation, and delivery. • Work with Spark and Databricks using a medallion architecture (Bronze/Silver/Gold). • Orchestrate workflows and data pipelines. • Ensure data quality, governance, and observability. • Optimize processing performance and costs. • Contribute to engineering best practices, version control, and documentation. • Support BI, Analytics, and AI teams and projects with reliable, well-organized data. • Work for a leading B2B distributor of electrical materials, solutions, and related services.

🎯 Requirements

• Bachelor’s degree in Information Technology, Engineering, or a related field. • Experience in data engineering and ETL/ELT pipeline development. • Proficiency in Python and advanced SQL. • Experience with Spark and Databricks. • Knowledge of Lakehouse/Data Lake architecture. • Experience with orchestration tools such as Apache Airflow. • Knowledge of analytical data modeling (Star Schema, Snowflake, OBT, among others). • Experience with dbt for data transformation and modeling. • Experience with data ingestion and integration tools (e.g., Azure Data Factory, Airbyte). • Proficiency with Git and software development best practices. • Preferred: Experience with Azure Cloud. • Preferred: Experience with Power BI and analytical environments. • Preferred: Experience with CI/CD, observability, and data quality.

🏖️ Benefits

• Professional development opportunities • Dynamic work environment • An environment that fosters innovation, collaboration, and enhanced career opportunities • Equal employment opportunities • Affirmative action positions for people with disabilities