Position Overview:
The Data Reliability Engineer II is an integral part of the Data Operations (DataOps) Team, responsible for analyzing and externalizing DoubleVerify’s data internally as well as monitoring, troubleshooting and improving the various company’s data pipelines and technologies.
Responsibilities:
- You will gain in-depth knowledge of how data is collected, processed and externalized to clients within DoubleVerify’s architecture
- You will script in python and SQL extensively
- You will be working with data analysis tools such as Splunk to create reports and data visualization
- You will be part of the on-call rotation
- You will work with Vertica, OLTP, and Hive/SparkSQL
- You are also thrilled at the prospect of building strong relationships with different teams in the company, solving operational issues and implementing quality improvements
Requirements:
- Bachelor's degree in CS or equivalent technical experience. Degree in a technical field preferred
- Strong SQL querying skills
- 2+ years SQL experience
- Demonstrated ability to quickly adapt, learn new skill sets, and be able to understand operational challenges
- Strong analytical, problem-solving, negotiation and organizational skills with a clear focus under pressure
- Must be proactive with proven ability to execute on multiple tasks simultaneously
- Resourceful, results orientated with the ability to get things done and overcome obstacles
- Excellent interpersonal skills, including relationship building with diverse, global, cross-functional team
- Proven ability to troubleshoot and problem solve in complex systems
- 2+ years Linux environment experience
- Good understanding of BI and Data Warehousing concepts (ETL, OLAP vs. OLTP, Slowly Changing Dimensions)
- Good understanding of process automation
- 2+ years of experience writing SQL and scripting languages python , bash, etc
Nice to have:
- Cloud computing fundamentals, knowledge of Google Cloud services
- Previous experience with Gitops, CI/CD, Gitlab or other automation/delivery tools