Senior Data Engineer, Databricks

Job not on LinkedIn

🔥 14 hours ago

🇧🇷 Brazil – Remote

⏰ Full Time

🟠 Senior

🚰 Data Engineer

👻 Ghost score 25%

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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Compass

WebsiteLinkedInAll Job Openings

10,000+ employees

🏠 Real Estate

📱 Media

Real Estate • Media

Compass is a real-estate-focused content and services site that provides detailed market analysis, buying/selling/renting guides, mortgage and financing information, and home improvement and renovation advice. The site offers resources for homebuyers, sellers, renters, agents, and real estate investors — including articles on appraisals, affordable housing, investment strategies, staging and property maintenance. Compass aims to help users make informed decisions across the housing lifecycle through timely market updates and practical how-to content.

📋 Description

• Define and implement Data Engineering solutions, connecting business needs with technology • Design and build data architectures, including Data Lake and Data Lakehouse environments • Develop and manage scalable data pipelines for both batch and streaming processing • Assess and analyze data collection, organization, transformation, and delivery processes • Ensure data quality, governance, security, and performance • Partner with Data and Business teams to support decision-making • Define data strategies aligned with business objectives • Mentor Data Engineering professionals

🎯 Requirements

• Solid experience in Data Engineering and data architecture • Advanced knowledge of Azure Data Factory and Databricks • Experience with Apache Spark and distributed processing • Experience building batch and streaming pipelines • Knowledge of orchestration tools such as Airflow • Knowledge of Kafka and dbt • Experience with SQL and NoSQL databases, including PostgreSQL, MongoDB, and Cassandra • Knowledge of cloud data platforms and services, including AWS and GCP • Experience with Data Lake and Data Lakehouse architectures • Knowledge of data governance, quality, and security practices