Key Responsibilities:

Design, build, and maintain highly available and scalable data infrastructure to support our data processing and storage needs.
Develop and implement data reliability strategies and best practices to ensure the integrity and accuracy of our data.
Monitor data systems and proactively identify and resolve any issues that may arise.
Collaborate with data engineers to optimize data pipelines and implement automated processes for data validation and quality control.
Work closely with operations teams to identify and address any performance bottlenecks or system failures.
Stay up-to-date with the latest data technologies and tools and make recommendations for improvements and enhancements to our data infrastructure.
Document and maintain data reliability processes, procedures, and standards.
Participate in on-call rotations and respond to any data-related incidents in a timely manner.

Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field.
Minimum of 3 years of experience working with large-scale data systems.
Strong experience with data infrastructure and cloud-based technologies such as AWS, Azure, or Google Cloud Platform.
Proficient in programming languages such as Python, Java, or Scala.
Experience with data warehouses, ETL processes, and data modeling.
Knowledge of database technologies such as SQL, NoSQL, and Hadoop.
Excellent problem-solving and troubleshooting skills.
Strong attention to detail and ability to work in a fast-paced, dynamic environment.
Excellent communication and collaboration skills.

As a Data Reliability Engineer, you will have the opportunity to work with cutting-edge technologies and make a significant impact on our data-driven culture. If you are passionate about data and have a strong desire to build and maintain reliable data systems, we want to hear from you!

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