Responsibilities:

Design, implement and maintain highly reliable and scalable data systems that support our business needs and ensure maximum uptime.
Collaborate with cross-functional teams to identify and understand data requirements and translate them into technical solutions.
Develop and maintain monitoring systems to proactively identify potential issues and troubleshoot them in a timely manner.
Continuously analyze and optimize data systems for performance, scalability, and reliability.
Work closely with the software engineering team to ensure that data pipelines and ETL processes are efficient and reliable.
Lead the development and implementation of disaster recovery and backup strategies.
Develop and maintain documentation for data systems and processes for internal and external stakeholders.
Keep up-to-date with the latest technologies and trends in data engineering and recommend and implement improvements to our systems.

Qualifications:

Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred.
8+ years of experience in data engineering, data infrastructure, or a related field.
Strong experience with cloud-based data platforms such as AWS, Azure, or Google Cloud.
In-depth knowledge of data warehousing, ETL processes, and data modeling.
Proficiency in programming languages such as Python, Java, or Scala.
Experience with data pipeline tools like Apache Airflow, Luigi, or AWS Data Pipeline.
Proven experience in building and maintaining highly available and scalable data systems.
Strong problem-solving skills and ability to troubleshoot complex issues.
Excellent communication and collaboration skills.
Ability to work in a fast-paced and dynamic environment.

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