Senior Data Engineer, Databricks

Job not on LinkedIn

🔥 4 minutes ago

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

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

• Implement and evolve the Corporate Data Platform (Enterprise Lakehouse); • Participate in modernizing the corporate analytics ecosystem, migrating workloads from Azure to AWS and Databricks; • Develop, maintain and evolve scalable, reliable and high-performance data pipelines; • Build data ingestion, transformation and delivery solutions using Lakehouse architecture; • Implement Data Engineering standards, DataOps, CI/CD and code versioning; • Support data governance, data quality and data cataloging initiatives; • Refactor legacy pipelines into modern solutions based on Apache Spark and Databricks; • Work on complex integrations between corporate systems, ensuring scalability, governance and data reliability; • Collaborate in implementing Data Lake, Data Warehouse and Lakehouse architectures in Cloud environments.

🎯 Requirements

• Advanced SQL proficiency; • Experience building ETL/ELT pipelines; • Hands-on experience with Databricks; • Knowledge of Apache Spark; • Experience with Data Lake, Data Warehouse and/or Lakehouse architectures; • Knowledge of analytical and dimensional data modeling; • Experience processing large volumes of data; • Experience with Cloud environments, preferably AWS; • Knowledge of AWS Glue, Unity Catalog and Lake Formation; • Experience with Git and code versioning; • Knowledge of CI/CD practices applied to Data Engineering; • Experience with tools such as Airflow, Kafka and dbt; • Knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB and Cassandra); • Experience in modernization and migration projects for corporate data platforms; • Ability to work on complex integrations between corporate systems and distributed environments.

🏖️ Benefits

• Remote work