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Homes 4 Rent
Homes 4 Rent
11 – 50 कर्मचारी
आतिथ्यपरामर्शलॉजिस्टिक्स
Homes 4 Rent दक्षिण-पूर्वी क्वींसलैंड में आवासीय संपत्ति प्रबंधन सेवाएँ देने वाली एक स्वतंत्र स्वामित्व वाली एजेंसी है। कंपनी विशेष रूप से किराये की संपत्तियों के साथ काम करती है और मकान-मालिकों को उनकी आवश्यकताओं के अनुरूप सक्रिय प्रबंधन तथा किरायेदारों को स्पष्ट और तत्पर संवाद प्रदान करती है। इसका ऑनलाइन प्लेटफ़ॉर्म मकान-मालिकों और किरायेदारों, दोनों को संपत्ति संबंधी जानकारी, दस्तावेज़ों और वित्तीय रिपोर्टों तक चौबीसों घंटे पहुँच देता है। किराया प्रबंधन प्रक्रिया के हर चरण में Homes 4 Rent का दृष्टिकोण पेशेवर सेवा, ईमानदारी, विश्वास और व्यावहारिक पारदर्शिता पर आधारित है।
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कंपनी की नौकरियाँ

Senior Data Engineer, Onsite - Las Vegas

Build scalable data platforms and pipelines for single-family rental and homebuilding operations. Support business intelligence, AI/ML, data products, and data-informed decisions.

USसंयुक्त राज्यNVनेवादाTXटेक्सासUTयूटा
$1,21,116 – $1,51,395 / वर्ष
ऑन-साइटपूर्णकालिकवरिष्ठआवश्यक भाषा: अंग्रेज़ीडेटा इंजीनियर
ApacheAWSAzureIoTKafkaNoSQLPythonSparkSQLTableauक्लाउड

विवरण

  • Build and maintain real-time and batch pipelines for large-scale data processing and analysis.
  • Create tools for ingesting, curating, and provisioning complex first-party and third-party data.
  • Develop advanced data products and intelligent APIs.
  • Test, troubleshoot, integrate features, and monitor system performance.
  • Lead data analysis and architecture work for BI, AI/ML, and data products.
  • Design and implement data platform architecture aligned with analytical needs.
  • Create solutions that support scalability, maintainability, extensibility, flexibility, and integrity.
  • Provide technical direction and mentorship to team members.
  • Lead peer development and code reviews emphasizing test-driven development and CI/CD.
  • Partner with business and cross-functional teams to convert requirements into scalable data solutions.
  • Enhance data models used by business intelligence tools and data-driven decision-making.
  • Deploy machine learning models into production.

आवश्यकताएँ

  • A required bachelor’s degree in computer science, information systems, data science, management information systems, mathematics, physics, engineering, statistics, economics, or a related field.
  • A related master’s degree is preferred.
  • At least eight years of data engineering experience with full-stack capabilities.
  • At least ten years of programming experience.
  • At least five years of experience with cloud platforms such as Azure, AWS, or Google Cloud.
  • Strong SQL skills.
  • Machine learning and ML pipeline experience is a plus.
  • Experience with real-time integration, intelligent applications, and data products.
  • Proficiency in Python and experience with CI/CD practices.
  • A strong background in infrastructure-as-a-service platforms.
  • Hands-on experience with Databricks, Spark, Fabric, or comparable technologies.
  • Experience working with Agile methodologies.
  • Hands-on experience designing and developing data pipelines and data products.
  • Experience building ingestion, processing, and analytical pipelines for big data, NoSQL, and data warehouse environments.
  • Hands-on experience with Azure data migration and processing services, including ADLS, Azure Data Factory, Event Hub, IoT Hub, Azure Stream Analytics, Azure Analysis Service, HDInsight, Databricks Azure Data Catalog, Cosmos DB, ML Studio, and AI/ML.
  • Extensive experience with big data technologies such as Apache Spark and streaming platforms such as Kafka and EventHub.
  • Extensive experience designing data applications in cloud environments.
  • Intermediate experience with RESTful APIs, messaging systems, and AWS or Microsoft Azure.
  • Extensive experience in data architecture and data modeling.
  • Expertise in data analysis and data quality frameworks.
  • Knowledge of business intelligence tools such as Power BI and Tableau.
  • Availability to work occasional evenings and/or weekends.

लाभ

  • Discretionary annual bonus.
  • Medical insurance.
  • Dental insurance.
  • Vision insurance.
  • Flexible spending accounts.
  • Health savings accounts.
  • Dependent savings accounts.
  • 401(k) plan with company matching contributions.
  • Employee stock purchase plan.
  • Tuition reimbursement program.
  • Nine paid holidays per year.
  • Paid time off accrued at 0.0577 hours per hour worked, up to 120 hours annually.

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