Senior Data Engineer, Analytics

Remote

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GitLab

The Data Engineer, Analytics role sits at the intersection of Analytics, Data Engineering, and Business Intelligence - serving as a technical expert who translates business needs into highly efficient data products. The Data Team is responsible for architecting and transforming raw data to self-service dashboards that business stakeholders can use to derive People and Engineering Insights. In this role, you'll have an opportunity to drive impact on a large scale by delivering trusted, transformed data that Senior Leadership will use to power the People and Engineering business decisions at GitLab.

 

Responsibilities 

  • Collaborate with other functions across the company by building reports and dashboards with useful analysis and data insights
  • Explain trends across data sources, potential opportunities for growth or improvement, and data caveats for descriptive, diagnostic, predictive (including forecasting), and prescriptive data analysis
  • Deep understanding of how data is created and transformed through GitLab products and services provided by third-parties to help drive product designs or service usage or note impacts to data reporting capabilities
  • Understand and document the full lifecycle of data and our common data framework so that all data can be integrated, modeled for easy analysis, and analyzed for data insights
  • Document every action in either issue/MR templates, the handbook, or READMEs so your learnings turn into repeatable actions and then into automation following the GitLab tradition of handbook first!
  • Expand our database with clean data (ready for analysis) by implementing data quality tests while continuously reviewing, optimizing, and refactoring existing data models
  • Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale database environment. Maintain and advocate for these standards through code review
  • Contribute to and implement data warehouse and data modeling best practices, keeping reliability, performance, scalability, security, automation, and version control in mind
  • Follow and improve our processes and workflows for maintaining high quality data and reporting while implementing the DataOps philosophy in everything you do

 

Requirements

  • A minimum of 3-5 years experience in a similar role
  • Advocate for improvements to data quality, security, and query performance that have particular impact across your team as a Subject Matter Expert (SME)
  • Solve technical problems of high scope and complexity
  • Exert influence on the long-range goals of your team
  • Understand the code base extremely well in order to conduct new data innovation and to spot inconsistencies and edge cases
  • Experience with performance and optimization problems, particularly at large scale, and a demonstrated ability to both diagnose and prevent these problems
  • Help to define and improve our internal standards for style, maintainability, and best practices for a high-scale web environment; Maintain and advocate for these standards through code review
  • Represent GitLab and its values in public communication around broader initiatives, specific projects, and community contributions
  • Provide mentorship for Junior and Intermediate Engineers on your team to help them grow in their technical responsibilities
  • Deliver and explain data analytics methodologies and improvements with minimal guidance and support from other team members. Collaborate with the team on larger projects
  • Build close relationships with other functional teams to truly democratize data understanding and access
  • Influence and implement our service level framework SLOs and SLAs for our data sources and data services
  • Identifies changes for the product architecture and from third-party services from the reliability, performance and availability perspective with a data driven approach focused on relational databases, knowledge of another data storages is a plus
  • Proactively work on the efficiency and capacity planning to set clear requirements and reduce the system resources usage to make compute queries cheaper
  • Participate in Data Quality Process or other data auditing activities

Also, we know it’s tough, but please try to avoid the ​​confidence gap​.​​ You don’t have to match all the listed requirements exactly to be considered for this role.

Hiring Process

To view the full job description and hiring process, please view our​ ​handbook​. Additional details about our process can also be found on our ​hiring page​.

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