Senior Data Engineer - Data Insights (Remote)

March 15

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Cloudbeds

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More Reservations. Happier Guests.

Technology • Software • Hotels • Property Management Software • Hostels

501 - 1000

Description

• Cloudbeds provides the platform that powers hospitality, driving streamlined operations, increasing reservations and revenue, and enabling memorable guest experiences for lodging businesses of all sizes and types • Named the No. 1 PMS and No. 1 Hotel Management System by Hotel Tech Report in 2022 • Cloudbeds is trusted by properties across the globe for its award-winning front desk, revenue, distribution, guest acquisition and guest engagement solutions seamlessly combined in a single unified system • From data architects to UX designers, integrations managers to payments experts, former hotel managers to former OTA executives, our team comprises the brightest minds in technology and hospitality working to solve the industry’s biggest challenges • From the beginning, we've believed that our people are our greatest asset, so we founded the company as #RemoteFirst, #RemoteAlways with shared core values that allow our team to thrive

Requirements

• BS or MS in computer science or a related technical field • Proven experience as a big data engineer or a similar role, with a deep understanding of big data technologies, frameworks, and best practices • Designing and implementing large-scale, distributed data processing systems using technologies such as Apache Hadoop, Apache Spark, or Apache Flink • Developing and optimizing data pipelines and workflows for ingesting, storing, processing, and analyzing large volumes of structured and unstructured data • Building and maintaining data infrastructure, including data lakes, data warehouses, and real-time streaming platforms • Designing and implementing data models and schemas for efficient data storage and retrieval • Ensuring the scalability, availability, and fault-tolerance of big data systems through proper configuration, monitoring, and performance tuning • Identifying and evaluating new technologies, tools, and frameworks to improve the efficiency and effectiveness of big data processing • Implementing data security and privacy measures to protect sensitive information throughout the data lifecycle • Knowledge of distributed computing principles and technologies, such as HDFS, YARN, and containerization (e.g., Docker, Kubernetes) • Understanding of real-time streaming technologies and frameworks, such as Kafka (Confluent) or Apache Flink • Strong problem-solving skills and ability to optimize and tune big data processing systems for performance and scalability • Excellent communication and teamwork skills to collaborate with cross-functional teams and stakeholders

Benefits

• Hire the best people around the world • Emphasize the value of results over hours put in • Provide flexibility in working hours and locations • Foster an inclusive environment that celebrates bold thinking and diverse perspectives • Offer open vacation policies, free LinkedIn Learning, and other benefits that promote well-being and professional development