At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

The Data Office is responsible for data associated with products, AI, marketing, finance, sales, and more. Our department ensures that all teams at JetBrains have access to up-to-date, reliable, and transparent data and data services.

As part of our growth strategy, we are looking for an experienced, detail-oriented, and self-motivated BI Analyst to develop, maintain, and enhance BI reports and dashboards for our internal customers across corporate functions, including marketing, IT, PMO, and others.

As part of our team, you will:

• Design, develop, and automate reports and dashboards for several of our data domains, such as marketing, IT, and executive reporting.
• Partner with the Data Quality team to define and implement rules that ensure high data reliability standards.
• Continuously engage with other colleagues at JetBrains, including team clients, data partners, data engineers, and data analysts, to gather and refine business requirements.
• Promote best practices in data visualization.
• Participate in both business-driven and technical projects.

We’ll be happy to have you on our team if you have:

• Extensive SQL experience.
• At least three years of experience with Tableau – experience with Metabase or alternative BI tools is a plus.
• Strong knowledge of and experience with dbt.
• Strong attention to detail and the ability to identify small but important differences.
• Ability to work independently, take ownership of tasks, analyze problems, and deliver results within agreed-upon deadlines.
• Fluent English, both written and spoken.
• Proactive mindset.
• Dedication to knowledge sharing and cross-team collaboration.

We’ll be especially thrilled if you have:

• Basic experience in DWH development.
• Basic experience with AWS. 
• Experience in marketing, including marketing metrics, data structures, and marketing data.

Why join JetBrains? 

• Strong base salary. We offer competitive pay that reflects your skills and experience.
• Flexible work location. Enjoy the freedom to work from home or from the office.
• Remote work. Spend up to 30 days per year working remotely from abroad.
• Extra time off. More days to relax, recharge, and do the things you love.
• Medical insurance allowance. Enjoy peace of mind for you and your family
• Learning and development opportunities. Access to conferences, courses, and language classes.
• Relocation support. We help make your move as smooth and stress-free as possible. 
• Language classes. Pick up the local language or sharpen your English skills.
• Fuel your day. Enjoy a hot meal or receive a lunch allowance on workdays.
• Mental health support. To help you feel your best, we provide easy access to professional mental health services.
• Sports benefit. Enjoy an on-site gym or sports club stipend.
• Internal events. Join company-wide celebrations and team gatherings.

*Some benefits may vary depending on location.

#LI-DNI

#LI-KP1

We're building an AI copilot for web testing automation. It enables manual and automation QA engineers to turn their manual testing flows into production-ready automated E2E testing scripts, saving hours of manual work and coding. We are a small team with zero bureaucracy, focusing on real users. We optimize for shipping value - not hype.

About the role:

You'll own the top of the funnel: outbound, qualification, and getting leads to sit down for a conversation. Demos, onboarding, and retention are staying with the founder for now.

Phase one: Get individual Automation QAs to try the product, aiming for fast adoption and no procurement. Once we hit 20+ weekly users, we’ll move on to phase two, where we’ll shift the focus to B2B – qualified meetings with QA Leads and Engineering Managers.

Your focus in the first three months:

• Build targeted lists: Automation QAs at companies with web products and Playwright, Cypress, or Selenium in their stack.
• Run outbound sequences (LinkedIn is the baseline, but you decide the channels). A/B test weekly.
• Design qualification gates (forms and scoring) to filter leads before the founder calls.
• Reach 20+ weekly active users after month one – ICP-qualified and giving direct feedback to engineering.
• Document what works into a repeatable playbook.

Growth path:

This role expands as your strategies deliver results. Once the user pipeline works, you can take over demos and run B2B sales end to end. From there, the natural next step is Growth Lead (funnel optimization and scaling the playbook) or Account Executive (owning deal execution).

Why to join:

• You'll be building a strategy that scales the product, not filling a quota. What you create from scratch becomes the foundation.
• Your outreach turns into users who talk directly to engineering, and their feedback ships as features within days.
• AI for developer tools is a market with real pull, and QA automation is one of its sharpest pain points.
• We’re backed by JetBrains – financially secure with no reliance on external VC funding.

Who we're looking for:

You should have a high level of agency and be quant-minded – you live in funnel metrics, run experiments, and are comfortable saying "no" to leads that are a bad fit. 

The ideal candidate will:

• Have done 0-to-1 outbound for an early-stage devtool, QA tool, infrastructure product, or similar.
• Have proven cold outbound results, instead of being dependent on warm inbound.
• Be able to talk credibly about flaky tests, CI pain, and Playwright vs. Cypress. You don't need to be an engineer, but you do need domain empathy.
• Possess strong written communication skills, with the ability to craft short, sharp messages that get replies.

Nice to have:

• A QA or SDET background – you've felt the pain yourself before moving to sales or BD.
• Exposure to security/compliance objections – enough to pre-empt and route.
• Content skills – your LinkedIn posts get engagement, not just your DMs.
• Experience as one of the first 10 employees at a startup.

#LI-REMOTE 
#LI-KT1

• Partner with Sales stakeholders to define analytical requirements, metrics, and KPIs, and identify opportunities for improvement.
• Develop and maintain dashboards, reports, and visualizations that provide timely and actionable insights.
• Analyze revenue streams and contribute to forecasting using statistical, heuristic, or machine learning approaches.
• Perform exploratory and ad hoc analyses to support decision-making across Sales and related teams.
• Collaborate with data engineers to design and implement data marts, reporting layers, and ETL pipelines; contribute to our dbt-based analytics infrastructure.
• Support Sales Development and Lead Generation teams by analyzing experiments and campaign performance.
• Monitor data quality across reporting assets and work with data owners to resolve issues.
• Document metrics, dashboards, and data sources, and help stakeholders effectively use analytics tools.
• Promote self-service analytics by enabling teams to access and interpret data independently.

• Proven years of experience in a BI, data analysis, or similar analytical role.
• Strong SQL skills and experience with Python, R, or another relevant programming language.
• Experience with BI and visualization tools such as Tableau, Power BI, Qlik, DataLens, or similar.
• Understanding of data warehousing concepts, relational databases, and data processing workflows.
• Experience working with structured datasets and building reliable reporting solutions.
• Strong analytical thinking, attention to detail, and curiosity about data.
• Ability to communicate clearly with both technical and non-technical stakeholders.
• Professional working proficiency in English.

• Experience working with Sales, Marketing, or other go-to-market domains, especially in B2B environments.
• Hands-on experience building ETL pipelines and preparing datasets for analytics.
• Experience working with dbt or similar data transformation tools.
• Familiarity with data governance and data quality practices.

#LI-DNI

• Partner with Sales stakeholders to define analytical requirements, metrics, and KPIs, and identify opportunities for improvement.
• Develop and maintain dashboards, reports, and visualizations that provide timely and actionable insights.
• Analyze revenue streams and contribute to forecasting using statistical, heuristic, or machine learning approaches.
• Perform exploratory and ad hoc analyses to support decision-making across Sales and related teams.
• Collaborate with data engineers to design and implement data marts, reporting layers, and ETL pipelines; contribute to our dbt-based analytics infrastructure.
• Support Sales Development and Lead Generation teams by analyzing experiments and campaign performance.
• Monitor data quality across reporting assets and work with data owners to resolve issues.
• Document metrics, dashboards, and data sources, and help stakeholders effectively use analytics tools.
• Promote self-service analytics by enabling teams to access and interpret data independently.

• 5+ years of experience in a BI, data analysis, or similar analytical role.
• Strong SQL skills and experience with Python, R, or another relevant programming language.
• Experience with BI and visualization tools such as Tableau, Power BI, Qlik, DataLens, or similar.
• Understanding of data warehousing concepts, relational databases, and data processing workflows.
• Experience working with structured datasets and building reliable reporting solutions.
• Strong analytical thinking, attention to detail, and curiosity about data.
• Ability to communicate clearly with both technical and non-technical stakeholders.
• Professional working proficiency in English.

• Experience working with Sales, Marketing, or other go-to-market domains, especially in B2B environments.
• Hands-on experience building ETL pipelines and preparing datasets for analytics.
• Experience working with dbt or similar data transformation tools.
• Familiarity with data governance and data quality practices.

#LI-DNI