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Senior Data Engineer, Data Services

Posted 2024-08-10

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💎 Seniority level: Senior, 8+ years

📍 Location: Central EU or Americas, Pacific Time Zone, NOT STATED

🔍 Industry: Real estate investment

🏢 Company: Roofstock👥 501-1000💰 $240.0m Series E on 2022-03-10🫂 on 2023-03-22Rental PropertyPropTechMarketplaceReal EstateFinTech

🗣️ Languages: English

⏳ Experience: 8+ years

🪄 Skills: AWSDockerPythonSQLAgileETLSCRUMSnowflakeAirflowData engineeringgRPCRESTful APIsMicroservices

Requirements:
  • BS or MS in a technical field: computer science, engineering or similar.
  • 8+ years technical experience working with data.
  • 5+ years strong experience building scalable data services and applications using SQL, Python, Java/Kotlin.
  • Deep understanding of microservices architecture and RESTful API development.
  • Experience with AWS services including messaging and familiarity with real-time data processing frameworks.
  • Significant experience building and deploying data-related infrastructure and robust data pipelines.
  • Strong understanding of data architecture and related challenges.
  • Experience with complex problems and distributed systems focusing on scalability and performance.
  • Strong communication and interpersonal skills.
  • Independent worker able to collaborate with cross-functional teams.
Responsibilities:
  • Improve and maintain the data services platform.
  • Deliver high-quality data services promptly, ensuring data governance and integrity while meeting objectives and maintaining SLAs.
  • Develop effective architectures and produce key code components contributing to technical solutions.
  • Integrate a diverse network of third-party tools into a cohesive, scalable platform.
  • Continuously enhance system performance and reliability by diagnosing and resolving operational issues.
  • Ensure rigorous testing of the team's work through automated methods.
  • Support data infrastructure and collaborate with the data team on scalable data pipelines.
  • Work within an Agile/Scrum framework with cross-functional teams to deliver value.
  • Influence the enterprise data platform architecture and standards.
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