Data Analytics

Data Analyst Roles at GitLab

Read more about this role in the Data Analytics Handbook Page.

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
• Understand and document the full lifecycle of data in our Data Catalog so data can be efficiently integrated, modeled, and analyzed
• Develop new Trusted Data Tests to expand test coverage for the Enterprise Data Warehouse
• 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!
• 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
• Follow and improve our processes and workflows for maintaining high quality data and reporting while implementing the DataOps philosophy in everything you do

Requirements

• Ability to use GitLab
• Ability to thrive in a fully remote organization
• Share and work in accordance with our values
• Positive and solution-oriented mindset
• Clearly and concisely communicate complex business logic, technical requirements, and design recommendations through iterative solutions
• Fluent in SQL within analytical data warehouses (we use Snowflake SQL) and in business intelligence tools (we use Periscope)
• Able to write complex SQL including multi-table joins, grouping and aggregation, common table expressions, and conditional filters
• Passionate about data, analytics and automation. Experience cleaning and modeling large quantities of raw, disorganized data (we use dbt)
• Experience working with a variety of complex data sources. Our data includes Salesforce, Zuora, Zendesk, Marketo, NetSuite, Snowplow and many others (see the data team page)
• Effective communication and collaboration skills, including clear status updates
• Comfort working in a highly agile, intensely iterative environment
• Self-motivated and self-managing, with strong organizational skills
• Prior experience in an analytics role, or equivalent education

Levels

Data Analyst Intern

An intern is not required to meet the base Data Analyst responsibilities and requirements, but 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
• Organizational skills

What you'll do

• Work with and learn from a talented team of data professionals
• Develop and execute a project with the help of a mentor
• 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

Junior Data Analyst

The Junior Data Analyst reports to the Manager, Data.

Junior Data Analyst Job Grade

The Junior Data Analyst is a grade 5.

Junior Data Analyst Responsibilities

The responsibilities of the Junior Data Analyst are listed in the Responsibilities section above.

Junior Data Analyst Requirements

The Junior Data Analyst Requirements extend the Requirements section above and include:

• 1+ years experience in an analytics role or equivalent experience/training

Data Analyst (Intermediate)

The Data Analyst (Intermediate) reports to the Manager, Data.

Data Analyst (Intermediate) Job Grade

The Data Analyst (Intermediate) is a grade 6.

Data Analyst (Intermediate) Responsibilities

The responsibilities of the Data Analyst extend the Junior Data Analyst role and include:

• 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
• Serve as a Subject Matter Expert (SME) in one or more Data Sources and its related Business Subject
• Provide expertise to all GitLab teams through code reviews, pairing, and training to help deliver optimal queries in Snowflake and in Periscope
• Approve data model changes as a Data Team Reviewer and code owner for specific database and data model schemas

Data Analyst (Intermediate) Requirements

The requirements of the Data Analyst extend the Junior Data Analyst role and include:

• 2+ years experience in an analytics role or equivalent experience/training
• Hands on experience working with Python, API calls, and JSON, to generate business insights and drive better organizational decision making
• Demonstrated analytical experience with one or more of the following business subject areas: marketing, finance, sales, product, customer success, customer support, engineering, or people
• Demonstrated ability to define, design, and develop Key Performance Indicators related to one or more business subject areas

Senior Data Analyst

The Senior Data Analyst reports to the Manager, Data.

Senior Data Analyst Job Grade

The Senior Data Analyst is a grade 7.

Senior Data Analyst Responsibilities

The responsibilities of the Senior Data Analyst extend the Data Analyst (Intermediate) role and include:

• Build close relationships with other functional teams to truly democratize data understanding and access
• Solve technical problems of high scope and complexity
• Exert influence on the long-range goals of your team
• Advocate for improvements to data quality, security, and query performance that have particular impact across your team as a Subject Matter Expert (SME)
• Understand the code base extremely well in order to conduct new data innovation and to spot inconsistencies and edge cases
• Provide mentorship for Junior and Intermediate members of the team to help them grow in their 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

Senior Data Analyst Requirements

The requirements of the Senior Data Analyst extend the Data Analyst (Intermediate) role and include:

• 6+ years experience in an analytics role or equivalent experience/training
• Fluent in all Data Analysis technologies defined in in the Data Team Platform
• Recognized expert in SQL, Data Visualization and Business Intelligence
• Own and maintain one or more sections of the Data Catalog
• Own and maintain one or more sections of the Trusted Data Framework for a specified Trusted Model

Staff Data Analyst

The Staff Data Analyst reports to the Manager, Data.

Staff Data Analyst Job Grade

The Senior Data Analyst is a grade 8 and is equivalent to the Manager,Data (Intermediate) job grade.

Market Justification: The business need for this role is to hire, retain, and develop technical talent by establishing Individual Contributor focused career paths for our team members who do not want to move into Data People Management. Staff Data Analyst is a widely accepted role, as supported by survey data, and is common in many data-driven companies. In some companies this position is also called Lead Data Analyst.

Staff Data Analyst Responsibilities

The responsibilities of the Staff Data Analyst extend the Senior Data Analyst role and include:

• Help promote data innovation across GitLab with a willingness to experiment and to confront hard and complex problems
• Identify and resolve impediments to efficiency and enable the entire Data Program to iterate faster
• Act as a specialist in the Data Analytics industry and in GitLab by setting the strategic aims and the short term goals of the Data Team
• Provide mentorship for all analysts at GitLab to help them grow in their business and technical capabilities, remove blockers to their autonomy, and share your knowledge across the organization
• Create training guides, blog posts, templates, and recorded training sessions to help all at GitLab understand how to accurately view data, use data for insights, and the implications of data-driven analysis in conjunction with legal and security concerns
• Help create the sense of psychological safety in the department

Staff Data Analyst Requirements

The requirements of the Staff Data Analyst extend the Senior Data Analyst role and include:

• 8+ years experience in an analytics role or equivalent experience/training
• Fluent in all major technologies in the Data Team Platform, with a particular emphasis on Data Visualization, Business Intelligence and Data Modeling
• Recognized expert in SQL, Sisense, and dbt
• Influence the Analytics Roadmap for one of the Data Flywheels
• Own and maintain one or more sections of the Enterprise Data Platform

Specialties

Data Team

• 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 in Periscope
• Approve data model changes as a Data Team Reviewer and code owner for specific database and data model schemas
• Own the end-to-end process of on-call data triaging from reading Airflow logs, to diagnosing the data issue, and to verifying and implementing a solution with an automated alerting system (ChatOps, etc) as well as providing data support for all GitLab members
• This position reports to the Manager, Data

Engineering

• 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, Engineering but will collaborate with and reporting into the Data Team

Finance

• 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

Growth

• 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

Product

• Support the Product function by spearheading tracking and reporting initiatives
• Focus on product usage metrics across SaaS and self-managed products
• Build cross-functional analysis to drive strategic decision-making
• Priorities will be set by a Director of Product but will collaborate with and report into the Data Team

Sales

• Coordinate with SalesOps to improve and automate tracking potentially insightful data points
• Focus on cross-functional analysis 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

Marketing

Analyst

• Coordinate with Marketing to improve and automate tracking potentially insightful data points, by analyzing data and discovering insights
• Support Marketing by helping drive the standardization, capture, automation, and implementation of performance indicators
• Assist with data driven planning and strategy
• Focus on cross-functional analysis that can help drive marketing conversations
• Reports to Director of Marketing Strategy and Performance working closely with the Chief Marketing Officer
• Member of the Marketing Strategy and Performance Team

Web Analyst

• Provide recommendations for technical SEO improvements to the site.
• Implement our SEO strategy together with our marketing team and digital marketing agency.
• Grow traffic to about.gitlab.com through organic search marketing programs.
• Report on marketing site growth from SEO and paid search.
• Troubleshoot and formulate solutions to issues with SEO and site lead flow.
• Evaluate and report data across multiple channels to monitor marketing site growth. _ Additional Requirements_
• 3+ years in Search Engine Marketing role
• 1-3 years of enterprise software marketing experience.
• 3+ years experience Google Analytics (or related tool), Google Search Console and experience with at least one SEO tool.
• Technical/industry experience focused on SEO online advertising to improve lead generation, sales pipeline, and revenue.
• Reports to Director of Marketing Strategy and Performance working closely with the Chief Marketing Officer
• Member of the Marketing Strategy and Performance Team

People

• Coordinate and support the People function by automating all reports from Greenhouse, BambooHR, and Google Sheets into reporting dashboards.
• Focus on cross-functional analysis to help other departments identify opportunities for improvement within their recruiting, hiring, and retention policies.
• Priorities will be set by Director, People Operations but will collaborate with and report into the Data Team

Performance Indicators (PI)

• Adoption of Data Team BI charts throughout company
• % of issues requested triaged with first response within 36 hours (per business unit)

Career Ladder

The next step in the Data Analyst job family is to move to the Data Management job family.

Hiring Process

• 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 their 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 Senior Director, Data and Analytics or Managers, Data
• Next, candidates will be invited to schedule a second interview with the business division DRI
• Next, candidates will be invited to schedule a third interview with one a member from our Data team
• Next, candidates will be invited to schedule a fourth interview with a specialty Engineering manager

Additional details about our process can be found on our hiring page.

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About GitLab

GitLab Inc. is a company based on the GitLab open-source project. GitLab is a community project to which over 2,200 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, self-learning, frugality, collaboration, directness, kindness, diversity, inclusion and belonging, 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:

1. Mission: Everyone can contribute
2. Results: Fast growth, ambitious vision
3. Flexible Work Hours: Plan your day so you are there for other people & have time for personal interests
4. Transparency: Over 2,000 webpages in GitLab handbook, GitLab Unfiltered YouTube channel
5. Iteration: Empower people to be effective & have an impact, Merge Request rate, We dogfood our own product, Directly responsible individuals
6. Diversity, Inclusion & Belonging: A focus on gender parity, Team Member Resource Groups, other initiatives
7. Collaboration: Kindness, saying thanks, intentionally organize informal communication, no ego
8. Total Rewards: Competitive market rates for compensation, Equity compensation, global benefits (inclusive of office equipment)
9. Work/Life Harmony: Flexible workday, Family and Friends days
10. Remote Done Right: One of the world's largest all-remote companies, prolific inventor of remote best practices

See our culture page for more!