Senior Analytics Engineer
An overview of this role
Analytics Engineers sit at the intersection of business teams, Data Analytics and Data Engineering and are responsible for bringing robust, efficient, and integrated data models and products to life. Analytics Engineers speak the language of business teams and technical teams, they are able to translate data insights and analysis needs into models powered by the Enterprise Data Platform. The successful Analytics Engineer is able to blend business acumen with technical expertise and transition between business strategy and data development.
What You’ll Do
Serve as the Directly Responsible Individual for major sections of the Enterprise Dimensional Model
Design, develop, and extend dbt code to extend the Enterprise Dimensional Model
Approve data model changes as a Data Team Reviewer and code owner for specific database and data model schemas
Provide data modeling expertise to all GitLab teams through code reviews, pairing, and training to help deliver optimal, DRY, and scalable database designs and queries in Snowflake and Tableau.
Own one or more stakeholder relationship in Go To Market, Research & Development, or General & Administrative business functions
Serve as Data Model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately
Advocate for the Data Quality Program and Trusted Data to help ensure all data is profiled, reviewed, and accurate to support critical decisions
Guide Work Breakdown Sessions
Organize and Plan quarter-long development initiatives per the Data Team Planning Drumbeat
What You’ll Bring
6+ years in the Data space as an analyst, engineer, scientist, or equivalent
2+ years managing the same data model system over time, evolving the model to meet new business requirements
Demonstrated experience leading 4 or more analytics projects from beginning to operationalization
Demonstrated experience designing and socializing Entity Relationship Diagrams and reference SQL scripts to scale data acumen and adoption
Experience working with multiple commercial data warehouses, ETL tools, and data visualization tools
Extensive experience in 2 or more major data subject areas (marketing, sales, finance, product, people, etc.)
Ability to use GitLab
Ability to thrive in a fully remote organization
Positive and solution-oriented mindset
Comfort working in a highly agile, intensely iterative environment
Self-motivated and self-managing, with task organizational skills
Great communication: Regularly achieve consensus amongst technical and business teams
Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations
Demonstrated experience with one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people
How GitLab will support you
Home office support
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
The base salary range for this role’s listed level is currently for residents of listed locations only. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, and alignment with market data. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
California/Colorado/Hawaii/New Jersey/New York/Washington/DC/Illinois/Minnesota pay range
$97,400—$208,800 USD
About the job
Apply for this position
Senior Analytics Engineer
An overview of this role
Analytics Engineers sit at the intersection of business teams, Data Analytics and Data Engineering and are responsible for bringing robust, efficient, and integrated data models and products to life. Analytics Engineers speak the language of business teams and technical teams, they are able to translate data insights and analysis needs into models powered by the Enterprise Data Platform. The successful Analytics Engineer is able to blend business acumen with technical expertise and transition between business strategy and data development.
What You’ll Do
Serve as the Directly Responsible Individual for major sections of the Enterprise Dimensional Model
Design, develop, and extend dbt code to extend the Enterprise Dimensional Model
Approve data model changes as a Data Team Reviewer and code owner for specific database and data model schemas
Provide data modeling expertise to all GitLab teams through code reviews, pairing, and training to help deliver optimal, DRY, and scalable database designs and queries in Snowflake and Tableau.
Own one or more stakeholder relationship in Go To Market, Research & Development, or General & Administrative business functions
Serve as Data Model subject matter expert and data model spokesperson, demonstrated by the ability to address questions quickly and accurately
Advocate for the Data Quality Program and Trusted Data to help ensure all data is profiled, reviewed, and accurate to support critical decisions
Guide Work Breakdown Sessions
Organize and Plan quarter-long development initiatives per the Data Team Planning Drumbeat
What You’ll Bring
6+ years in the Data space as an analyst, engineer, scientist, or equivalent
2+ years managing the same data model system over time, evolving the model to meet new business requirements
Demonstrated experience leading 4 or more analytics projects from beginning to operationalization
Demonstrated experience designing and socializing Entity Relationship Diagrams and reference SQL scripts to scale data acumen and adoption
Experience working with multiple commercial data warehouses, ETL tools, and data visualization tools
Extensive experience in 2 or more major data subject areas (marketing, sales, finance, product, people, etc.)
Ability to use GitLab
Ability to thrive in a fully remote organization
Positive and solution-oriented mindset
Comfort working in a highly agile, intensely iterative environment
Self-motivated and self-managing, with task organizational skills
Great communication: Regularly achieve consensus amongst technical and business teams
Demonstrated capacity to clearly and concisely communicate complex business activities, technical requirements, and recommendations
Demonstrated experience with one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people
How GitLab will support you
Home office support
Please note that we welcome interest from candidates with varying levels of experience; many successful candidates do not meet every single requirement. Additionally, studies have shown that people from underrepresented groups are less likely to apply to a job unless they meet every single qualification. If you're excited about this role, please apply and allow our recruiters to assess your application.
The base salary range for this role’s listed level is currently for residents of listed locations only. Grade level and salary ranges are determined through interviews and a review of education, experience, knowledge, skills, abilities of the applicant, equity with other team members, and alignment with market data. See more information on our benefits and equity. Sales roles are also eligible for incentive pay targeted at up to 100% of the offered base salary.
California/Colorado/Hawaii/New Jersey/New York/Washington/DC/Illinois/Minnesota pay range
$97,400—$208,800 USD