Senior Data Engineer

🕒 April 21

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 30%

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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Data Meaning

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

📦 Logistics

☁️ SaaS

Consulting • Logistics • SaaS

Data Meaning is a company that specializes in accelerating analytical workloads for businesses, helping them to increase productivity and focus on high-value tasks. They offer managed services, expert-on-demand solutions, and enablement & training programs to help organizations handle increased workloads and embrace new technologies effectively. With over 20 years of experience and more than 800 projects completed, Data Meaning provides expertise in data governance and strategy, aligning data initiatives with business objectives. They target bottlenecks in productivity and offer solutions in sectors like public sector and other industries to improve efficiency and compliance. Their services are designed to help businesses outsource mundane tasks, increase team engagement, and boost work efficiency through specialized skills and frameworks.

📋 Description

• Develop and maintain ELT pipelines using Snowflake, Python, and Apache Airflow • Implement data ingestion and transformation logic for batch and incremental pipelines • Convert existing SQL transformations into dbt models • Implement dbt testing frameworks (schema, relationship, freshness tests) • Participate in pipeline walkthroughs and knowledge transfer sessions with the existing team • Document data pipelines and operational procedures • Support the transition from vendor-managed pipelines to Data Meaning ownership • Monitor production pipelines and data workflows • Troubleshoot pipeline failures and operational issues • Improve monitoring, alerting, and operational reliability • Implement automated data validation and quality checks • Support the development of a data quality framework

🎯 Requirements

• 8+ years of experience in Data Engineering • Hands-on experience with Snowflake • Experience working with Apache Airflow • Strong SQL (advanced) skills • Strong Python programming skills • Experience building: ELT pipelines, Data warehouse transformations, Batch and incremental pipelines, Data ingestion pipelines • Experience working in cloud environments (AWS preferred)

🏖️ Benefits

• Flexible work arrangements • Collaborative, inclusive, and innovation-driven work culture