Senior Data Engineer

About the role

Apply engineering best practices to analyze, design, develop, deploy, and support software solutions. Develop software using continuous deployment and integration practices, leveraging vendor-supplied solutions to fulfill organizational goals around large analytical and operational data platforms. Participate in Agile implementations and maintenance of source control and release procedures. Contribute to code reviews and provide feedback to the team. Explain technical solutions to technical teams.

Understand data platforms, data lake technology, and strategies to expand business use cases. Build and maintain a platform-level observability framework. Work with large data platforms in support of an enterprise data lake solution. Incorporate enterprise observability platforms into frameworks for logging, alerting, and monitoring to ensure scalability, reliability, and predictability. Assist in defining platform SLIs, SLOs, and SLAs. Identify data quality issues, determine root causes, propose fixes, and design data audits.

Responsibilities

• Develop and maintain software solutions using continuous deployment and integration practices.
• Participate in Agile implementations and source control/release procedures.
• Conduct code reviews and provide feedback to the team.
• Explain technical solutions to technical teams.
• Build and maintain a platform-level observability framework for logging, alerting, and monitoring.
• Work with large data platforms to support an enterprise data lake solution.
• Define platform SLIs, SLOs, and SLAs.
• Identify data quality issues, determine root causes, propose fixes, and design data audits.

Requirements

• Bachelor’s degree in Computer Science or a related field.
• Minimum of 4 years of experience as a data engineer or related occupation.
• At least 4 years of experience with each of the following:
  • Python, JVM (Java, Scala), Apache Spark, SQL, Terraform, and YAML configuration as code.
  • Agile methodologies and DevOps environments.
  • Data integration patterns and tooling, including ELT/ETL, EII, replication, event streaming, and virtualization to support batch and real-time data needs.
  • Enterprise data platforms in support of a data lake, including Airflow and Starburst.
  • Terraform.

Pay

Salary range: $113,922–$222,300 per year.

Benefits

• Flexible work schedules (telecommuting permissible).
• Concierge service.
• Comprehensive benefits.
• Employee resource groups.