Principal Data Engineer
Data Platform Team
Confirmed live in the last 24 hours

1,001-5,000 employees

Travel guidance platform
Oxford, UK
Experience Level
Desired Skills
Apache Spark
Apache Kafka
Data Analysis
Google Cloud Platform
Microsoft Azure
Data & Analytics
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field
  • Minimum of 8 years of hands-on experience in data engineering, with a focus on building large-scale data platforms and data processing pipelines
  • Proficiency in programming languages such as Python, Java, or Scala, and experience with big data technologies like Hadoop, Spark, and Kafka
  • Strong experience with cloud-based data platforms, such as AWS, GCP, or Azure, including services like S3, MSK, ECS, or equivalent
  • In-depth knowledge of data modeling, data warehousing, and ETL/ELT processes
  • Familiarity with data governance and security best practices and compliance standards
  • Proven experience in performance optimization and tuning of data pipelines and database queries
  • Excellent leadership and communication skills, with the ability to collaborate effectively with cross-functional teams
  • Experience in the travel industry or related domains is desirable but not mandatory
  • Data Pipeline Architecture: Design and develop scalable, reliable, and efficient data pipelines that facilitate the collection, ingestion, and processing of diverse data from various sources, ensuring high data quality and availability
  • Data Modeling and Warehousing: Create and optimize data models that enable seamless integration of data from multiple sources into a centralized data warehouse or data lake, enabling data access and analysis for different business units
  • Data Governance and Security: Establish data governance frameworks and implement robust data security measures to ensure compliance with privacy regulations and protect sensitive information
  • Performance Optimization: Continuously monitor and fine-tune the data platform's performance to meet SLAs and optimize resource utilization, ensuring smooth and fast data access for analytical needs
  • Technology Evaluation: Stay up-to-date with industry trends, emerging technologies, and best practices in data engineering. Assess and recommend new tools and frameworks to improve data processing capabilities
  • Team Leadership and Mentorship: Provide technical leadership and mentorship to a team of data engineers, fostering a collaborative and innovative work environment
  • Cross-Functional Collaboration: Collaborate with data analysts, data scientists, and software engineers to understand their data requirements, offer data engineering support, and contribute to the development of data-driven products and solutions
  • Data Quality and Monitoring: Implement robust data quality checks and monitoring systems to ensure the accuracy, consistency, and reliability of data
  • Documentation and Knowledge Sharing: Create and maintain comprehensive documentation of data engineering processes, best practices, and technical standards. Facilitate knowledge sharing sessions with the broader team
Desired Qualifications
  • Prior experience in mentoring and guiding junior data engineers is a plus