Senior Manager, Analytics Engineering
An overview of this role
The Senior Manager, Analytics Engineering (R&D) sits at the intersection of Business Strategy, Analytics Engineering, and Data Engineering and is responsible for leading a team that brings robust, efficient, and integrated data products to life. The Senior Manager, Analytics Engineering (R&D) speaks the language of business teams and technical teams, able to translate data insights and analysis needs into data models powered by the Enterprise Data Platform. The successful Senior Manager, Analytics Engineering (R&D) is able to blend business acumen with technical expertise and transition between business strategy and data development. In this role, the incumbent will have an opportunity to drive impact on a large scale by leading a team that delivers trusted data that is used by Senior Leadership to power Customer Product Adoption at GitLab.
What You’ll Do
Manage, lead, and develop a high-performance Analytics Engineering team specializing in Product Usage data, including day-to-day assignments, bi-weekly milestone planning, 1-1s, quarterly objectives, and annual reviews
Lead the development of sophisticated data models that transform complex event-level usage data from our product into actionable business insights
Player/Coach that can both lead a team of expert data modelers and make hands-on contributions to our most challenging Product Usage data transformations and modeling initiatives
Understand the big picture of product adoption and user behavior, demonstrating how your team's Product Usage data models support strategic decision-making through prioritization, planning, and advanced solutioning
Architect and oversee the implementation of scalable data pipelines that process high-volume, real-time product usage events into reliable, performant data models
Collaborate closely with Product, Engineering, and Business Strategy teams to translate complex usage patterns and behavioral analytics requirements into robust data model specifications
What You’ll Bring
Share our values, and work in accordance with those values
5+ years hands on experience in a data analytics/engineering/science role
2+ years hands on experience performing quantitative analysis to tackle business problems with a focus on feature and usage metrics to increase conversion and retention
1+ years hands on experience creating dimensional models composed of facts and dimensions
1+ years leading or managing a team of 3 or more data analysts/engineers/scientists
Demonstrate ability to understand and communicate end-to-end data systems: from compute to ELT to Reporting to Analysis
Exceptional experience creating and developing partnerships with internal team members towards delivery of impactful analytics solutions
Experience defining and executing project plans at the day, week, and month time spans
Demonstrably deep understanding of SQL and relational databases (we use Snowflake)
Experience working with large quantities of raw, disorganized data
How GitLab will support you
Senior Manager, Analytics Engineering
An overview of this role
The Senior Manager, Analytics Engineering (R&D) sits at the intersection of Business Strategy, Analytics Engineering, and Data Engineering and is responsible for leading a team that brings robust, efficient, and integrated data products to life. The Senior Manager, Analytics Engineering (R&D) speaks the language of business teams and technical teams, able to translate data insights and analysis needs into data models powered by the Enterprise Data Platform. The successful Senior Manager, Analytics Engineering (R&D) is able to blend business acumen with technical expertise and transition between business strategy and data development. In this role, the incumbent will have an opportunity to drive impact on a large scale by leading a team that delivers trusted data that is used by Senior Leadership to power Customer Product Adoption at GitLab.
What You’ll Do
Manage, lead, and develop a high-performance Analytics Engineering team specializing in Product Usage data, including day-to-day assignments, bi-weekly milestone planning, 1-1s, quarterly objectives, and annual reviews
Lead the development of sophisticated data models that transform complex event-level usage data from our product into actionable business insights
Player/Coach that can both lead a team of expert data modelers and make hands-on contributions to our most challenging Product Usage data transformations and modeling initiatives
Understand the big picture of product adoption and user behavior, demonstrating how your team's Product Usage data models support strategic decision-making through prioritization, planning, and advanced solutioning
Architect and oversee the implementation of scalable data pipelines that process high-volume, real-time product usage events into reliable, performant data models
Collaborate closely with Product, Engineering, and Business Strategy teams to translate complex usage patterns and behavioral analytics requirements into robust data model specifications
What You’ll Bring
Share our values, and work in accordance with those values
5+ years hands on experience in a data analytics/engineering/science role
2+ years hands on experience performing quantitative analysis to tackle business problems with a focus on feature and usage metrics to increase conversion and retention
1+ years hands on experience creating dimensional models composed of facts and dimensions
1+ years leading or managing a team of 3 or more data analysts/engineers/scientists
Demonstrate ability to understand and communicate end-to-end data systems: from compute to ELT to Reporting to Analysis
Exceptional experience creating and developing partnerships with internal team members towards delivery of impactful analytics solutions
Experience defining and executing project plans at the day, week, and month time spans
Demonstrably deep understanding of SQL and relational databases (we use Snowflake)
Experience working with large quantities of raw, disorganized data
How GitLab will support you