Data Reliability Engineer

2 weeks ago

Belfast, United Kingdom caia - Jobboard Full time

Data Reliability Engineer

Caia - Jobboard is seeking a skilled Data Reliability Engineer to join our team. As a Data Reliability Engineer, you will be responsible for ensuring the reliability, scalability, and efficiency of our data infrastructure on Google Cloud Platform (GCP).

Key Responsibilities:

  1. Automate data tasks on GCP using tools such as Terraform and KCC.
  2. Design, build, secure, and maintain data infrastructure, including data pipelines, databases, data warehouses, and data processing platforms on GCP.
  3. Measure and monitor the quality of data on GCP data platforms.
  4. Implement robust monitoring and alerting systems to proactively identify and resolve issues in data systems.
  5. Develop automation scripts and tools to streamline data operations and make them scalable to accommodate growing data volumes and user traffic.
  6. Optimize data systems to ensure efficient data processing, reduce latency, and improve overall system performance.
  7. Collaborate with data and infrastructure teams to forecast data growth and plan for future capacity requirements.
  8. Ensure data security and compliance with data protection regulations.

Requirements:

  1. Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or related field, or equivalent practical experience.
  2. Experience as a Data Site Reliability Engineer or a similar role, with a focus on data infrastructure management.
  3. Proficiency in data technologies, such as relational databases, data warehousing, big data platforms (e.g., Hadoop, Spark), data streaming (e.g., AWS, GCP, Azure).
  4. Ideally some programming skills in languages like Python, Java, or Scala, with experience in automation and scripting.
  5. Experience with data governance, data security, and compliance best practices.
  6. Understanding of software development methodologies and best practices, including version control (e.g., Git).
  7. Ideally a background in cloud computing and data-intensive applications and services, with a focus on Google Cloud Platform.
  8. 3+ years of experience in data engineering or data science.
  9. Experience with data quality assurance and testing.
  10. Ideally knowledge of GCP data services (BigQuery; Data Fusion; Google Cloud Storage).
  11. Understanding of logging and monitoring using tools such as Cloud Logging, ELK Stack, AppDynamics, New Relic, Splunk, etc.
  12. Proven ability to learn new technologies, including open source and cloud-native offerings.
  13. Knowledge of AI and ML tools is a plus.
  14. Google Associate Cloud Engineer or Data Engineer certification is a plus.

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