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- Data Analyst
- Expand our data warehouse with clean data, ready for analysis
- Understand and document the full lifecycle of data from numerous sources and how to model it for easy analysis
- Build reports and dashboards to help teams identify opportunities and explain trends across data sources
- Follow and improve our processes for maintaining high quality data and reporting
- Implement the DataOps philosophy in everything you do
- Collaborate with other functions to create useful analyses and democratize insights across the company
- Build upon and document our common data framework so that all data can be connected and analyzed
- This position reports to the Manager, Data
- 2+ years experience in an analytics role
- Deep understanding of SQL and analytical data warehouses (we use Snowflake)
- Hands on experience working with Python and SQL to generate business insights and drive better organizational decision making
- Experience building reports and dashboards in a data visualization tool
- Familiarity with git and the command line
- Passionate about data, analytics and automation. Experience cleaning and modeling large quantities of raw, disorganized data (we use dbt)
- Experience with a variety of data sources. Our data includes Salesforce, Zuora, Zendesk, Marketo, NetSuite, Snowplow and many others (see the data team page)
- Share and work in accordance with our values
- Successful completion of a background check
All of the responsibilities of a Data Analyst, plus:
- Advocate for improvements to analysis quality, security, and performance that have particular impact across your team and the organization
- Solve technical problems of high scope and complexity
- Exert influence on the overall objectives and long-range goals of your team
- Experience with performance and optimization problems, particularly at large scale, and a demonstrated ability to both diagnose and prevent these problems
- Represent GitLab and its values in public communication around broader initiatives, specific projects, and community contributions
- Provide mentorship for Junior and Intermediate Analysts on your team to help them grow in their technical responsibilities and remove blockers to their autonomy
- Confidently ship moderately sized analyses and transformation models 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
An intern is not required to meet the standards of an intermediate data analyst but she or he is required to be interested in developing in towards them.
An intern must:
- Have a track record of asking hard questions and thinking critically
- Self-starter committed to remote work and its intricacies
- Proactive, positive, energetic, customer service personality
- Ability to articulate in a clear, concise manner, disseminating complete and accurate information
- Ability to deal effectively with people of multi-cultural societies
- Attention to detail
- Strong organizational skills
What you'll do
- Work with and learn from a talented team of data professionals
- Develop and execute an independent project under direct mentorship
- Write blog posts about your learnings
- Update, maintain, and coordinate meetings
- Update the handbook using git and GitLab
- Identify Data team process weaknesses and blindspots
- Contribute fresh perspective and speak up where you can add value
How you'll ramp
By the 30 day mark…
- Helping lead definition-related conversations, acting as thought-leader to functional group
- Working independently in Periscope, writing SQL queries to produce dashboards
- Clear sense of where prioritization comes from
- Understands values/working the GitLab way
- Comfortable participating in triage rotation without a named backup
By the 60 day…
- Comfortable working with dbt
- Comfortable participating in triage rotation on own
- Contributing to internal conversations on data organization and structure
By the 90 day…
- Comfortable building a new data source from scratch
- Can direct team members to answers in the handbook/in Periscope
- Regularly contributing to documentation and housekeeping improvements for the team
- Can gather requirements, scope, and build analysis with little-to-no guidance from more senior analysts
- Support all departments in the engineering division by helping drive the standardization, capture, automation, and implementation of performance indicators
- Be intimately familiar with productivity metrics
- Priorities will be set by the VP, Enfineering but will collaborate with and reporting into the Data Team
- Support the FP&A team in driving financial and operational initiatives by analyzing data and discovering insights
- Focus on financial and operational specific data
- Priorities will be set by the Manager, Financial Planning and Analysis but will collaborate with and report into the Data Team
- Spend 80% of time supporting the FP&A team and spend the remaining 20% of time contributing to the Data Team
- The Manager, Financial Planning and Analysis will evaluate the analyst on 80% of the goals in the experience factor worksheet relating to supporting FP&A and the Manager, Data will evaluate the analyst on the remaining 20% of goals relating to supporting the Data Team
- Support the product management function in driving product growth, reducing churn, increasing user engagement by analyzing data and discovering insights
- Focus on product-specific data - usage ping, SaaS DB, Snowplow events
- Priorities will be set by a Product Manager, Growth but will collaborate with and report into the Data Team
- Support the Product function by spearheading tracking and reporting initiatives
- Focus on product usage metrics across SaaS and self-managed products
- Build cross-functional analyses to drive strategic decision-making
- Priorities will be set by a Director of Product but will collaborate with and report into the Data Team
- Coordinate with SalesOps to improve and automate tracking potentially insightful data points
- Focus on cross-functional analyses that can help drive sales conversations (e.g. product usage into renewal conversations)
- Priorities will be set by the sales function but will collaborate with and report into the Data Team
The Infrastructure Department is the primary responsible party for the availability, reliability, performance, and scalability of all user-facing services (most notably GitLab.com). Other departments and teams contribute greatly to these attributes of our service as well. In these cases it is the responsibility of the Infrastructure Department to close the feedback loop with monitoring and metrics to drive accountability.
The Data Analyst, Infrastructure is a key member of the Infrastructure team and works to enhance and improve our business operations and our forecasting and financial modeling capabilities, developing sound business practices within the Infrastructure Department to guide infrastructure resource utilization and associated costs optimizations over time, as well as tracking and modeling of all relevant KPIs.
Data Analyst, Infrastructure Responsibilities
- Develop infrastructure resource utilization and forecasting models to meet business and financial objectives
- Develop infrastructure financial models to provide data-driven guidance on cost decisions
- Interface with Finance, Legal and vendors to manage Infrastructure-related contracts
- Interface with Sales to understand sales pipeline and its effect on Infrastructure
- Develop and maintain Infrastructure-centric sales collateral as it relates to GitLab.com
- Manage service level framework (SLIs, SLOs, SLAs) and associated error budgets to meet business objectives for GitLab.com
- Manage Infrastructure's Performance Indicators
- Review Infrastructure business processes and policies and help enhance workflows in support of GitLab.com and Infrastructure-provided services to the rest of the company
- Develop a deep understanding of the infrastructure vendor landscape to help Infrastructure leaders select, work and optimize infrastructure usage
The Data Analyst, Infrastructure reports to the Director of Engineering, Infrastructure.
Data Analyst, Infrastructure Performance Indicators
Performance Indicators (PI)
Candidates for this position can expect the hiring process to follow the order below. Please keep in mind that candidates can be declined from the position at any stage of the process. To learn more about someone who may be conducting the interview, find her/his job title on our team page.
- Selected candidates will be invited to fill out a short questionnaire.
- Next, candidates will be invited to schedule a screening call with our Global Recruiters
- Next, candidates will be invited to schedule a first interview with our Manager, Data & Analytics
- Next, candidates will be invited to schedule a second interview with a Data Analyst
- Next, candidates will be invited to schedule a third interview with our Dir. of Business Operations
- Next, if applying for a specialty, candidates will be invited to schedule a fourth interview with our the specialty lead
- Finally, candidates may be asked to interview with our CEO
Additional details about our process can be found on our hiring page.
Please note that if we are actively hiring for a position, you will see it
listed on our jobs page, where all of our current openings are
advertised. To apply, please click on the name of the role you are
interested in, which will take you to our applicant tracking system (ATS),
Avoid the confidence gap; you do not have to match all the listed
requirements exactly to apply. Our hiring process is described in more
detail in our hiring handbook.
GitLab Inc. is a company based on the GitLab open-source project. GitLab is
a community project to which over 1,000 people worldwide have contributed.
We are an active participant in this community, trying to serve its needs
and lead by example. We have one vision: everyone can
contribute to all digital content, and our mission is to change all creative
work from read-only to read-write so that everyone can contribute.
We value results, transparency, sharing, freedom,
efficiency, frugality, collaboration, directness, kindness, diversity and inclusion,
boring solutions, and quirkiness. If these values match your personality,
work ethic, and personal goals, we encourage you to visit our
primer to learn more. Open source is our culture, our way of
life, our story, and what makes us truly unique.
Top 10 reasons to work for GitLab:
- Work with helpful, kind, motivated, and talented people.
- Work remote so you have no commute and are free to travel and move.
- Have flexible work hours so you are there for other people and free to plan
the day how you like.
- Everyone works remote, but you don't feel remote. We don't have a head
office, so you're not in a satellite office.
- Work on open source software so you can interact with a large community and
can show your work.
- Work on a product you use every day: we drink our own wine.
- Work on a product used by lots of people that care about what you do.
- As a company we contribute more than we take, most of our work is released
as the open source GitLab CE.
- Focused on results, not on long hours, so that you can have a life and
don't burn out.
- Open internal processes: know what you're getting in to and be assured
we're thoughtful and effective.
See our culture page for more!
Work remotely from anywhere in the world. Curious to see what that looks
like? Check out our remote manifesto.