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

The Director of Data Engineering will lead and scale the Data Engineering and Analytics Engineering functions, owning the post-application data platform and its architecture, governance, and operating model. This foundational leadership role ensures best in class engineering standards, helps drive the organization toward a durable, auditable, data-product operating model, and modernizes and expands a Snowflake-centered data stack to include building and operating scalable distributed data processing and real-time streaming systems that support event-driven data products for operational use cases.

The role partners closely with Product, Software Engineering, Data Product Managers, Marketing, Compliance, Finance and Data Science to ensure our data ecosystem is production-grade, scalable, and compliant in a regulated gaming environment.

What You'll Do:

Team Leadership & Organizational Growth

• Lead and grow Data Engineering and Analytics Engineering teams; recruit, mentor, and elevate technical capabilities around distributed data processing, stream processing, and event-driven architectures
• Define ownership models for platform components and data products; set performance and hiring plans.
• Advance engineering standards for deployment: development, testing, documentation, release management, and SLAs.
• Partner with Data Product Managers to define data assets as versioned, documented data products with clear ownership and SLAs.

Platform, Architecture & Engineering Excellence

• Own the administration, reliability, governance, and strategic expansion of the Snowflake-based post-application data platform to operate scalable distributed data processing pipelines capable of handling high-volume event data across both batch and streaming workloads.
• Manage platform governance, access control, security, cost, and capacity planning.
• Standardize DBT deployment methods, promotion workflows, and environment management.
• Implement Infrastructure-as-Code (Terraform or similar) for reproducible, auditable infrastructure.
• Deliver monitoring, observability, lineage, and data quality frameworks; enforce traceability and auditability for regulated reporting.
• Own and evolve ingestion and warehouse architecture and transformation frameworks .
• Improve performance, cost efficiency, reliability, and scalability of data transformation and storage layers.
• Define and enforce engineering standards across the data lifecycle and establish SLAs and reliability metrics for critical assets - ensuring all pipelines, transformations, and reporting are auditable and documented for internal and external review

Event-Driven Architecture & Player 360

• Partner with Software Engineering on event messaging, streaming architecture, and ingestion patterns (built on technologies such as Kafka, Kinesis, Spark Structured Streaming, Flink, or equivalent platforms).
• Lead technical design and development of a unified Player 360 data foundation that integrates transactional, behavioral, and event-level data.
• Align application schema design with downstream analytical, product, and regulatory requirements.
• Balance real-time and batch processing strategies according to business needs and cost/complexity tradeoffs.

What You'll Bring:

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related STEM field preferred. Equivalent practical experience will be considered.
• 8+ years of experience in data engineering, with 3+ years of experience in leadership roles. 
• Experience transitioning an organization from private/startup to public company.
• Experience in regulated industries (gaming, fintech, payments, healthcare).
• Prior experience building Player 360 / Customer 360 platforms.
• Deep hands-on experience with Terraform / IaC and production-grade streaming systems (Kafka, Kinesis, etc.).
• Familiarity with GenAI governance frameworks and scalable AI integration patterns such as Harness Engineering.
• Able to travel occasionally both domestically and internationally. #LI-REMOTE #LI-PROMOTE

The Analytics Engineering Technical Lead will define and own the modeling architecture, standards, and technical direction within RSI’s cloud-native Data Platform. This role is accountable for ensuring that analytics-ready data is reliable, scalable, and aligned to long-term business needs across growth, operations, and risk.

You will lead the design and governance of core data models in Snowflake and dbt, establishing best practices that enable high-quality, self-service analytics without sacrificing trust or performance. As a hands-on technical leader, you will set standards for modeling, testing, documentation, and deployment while mentoring other Analytics Engineers and raising the overall technical bar of the team.

This role partners closely with Data Engineering, Analytics, and business stakeholders to translate evolving requirements into durable data products. You will help balance speed and governance, prioritize platform investments, and ensure our data foundation scales with the business.

Our modern data stack includes Snowflake, AWS, Python, Airflow, and dbt.

What You'll Do:

• Lead the design, development, and lifecycle management of curated datasets, dbt models, and analytics data marts aligned to business domains and metrics.
• Establish and evolve standards and best practices for dbt modeling, testing, documentation, and code organization to support long-term scalability.
• Ensure analytical datasets are accurate, reliable, and trusted, serving as a single source of truth for business, product, and stakeholders.
• Embed data quality checks, documentation, and governance directly into analytics pipelines.
• Partner closely with Product, Data Engineering and Analytics teams to translate business requirements into well-modeled, performant data products.
• Mentor and support Analytics Engineers through technical guidance, design reviews, and knowledge sharing.
• Continuously improve and modernize analytics workflows by introducing automation, tooling enhancements, and AI-assisted development where appropriate.
• This role includes technical leadership and mentoring responsibilities for the team, including other Analytics Engineers.

What You'll Bring:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related quantitative discipline.
• Technical Leadership: Proven experience defining technical direction, standards, and architectural decisions within analytics engineering or curation teams.
• Data Modeling Expertise: Deep understanding of dbt, data marts, dimensional modeling, and self-service BI enablement.
• Data Engineering Background: 7+ years of experience in data warehousing or development; 5+ years of experience in hands-on data engineering using SQL and Python.
• Cloud Infrastructure: Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization (Docker/Kubernetes).
• Tooling & Orchestration: Experience with tools like dbt, Airflow, S3, REST APIs, and large-scale DWHs (Snowflake, Redshift, BigQuery, etc.).
• Change Management: Skilled at leading cross-functional data initiatives and driving adoption of new tools and standards.
• People Leadership: Experience mentoring and guiding distributed teams across time zones.
• Communication: Strong written and verbal English skills with the ability to collaborate across technical and business functions.
• Able to travel occasionally both domestically and internationally #LI-HYBRID

• 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

Gambling.com Group (Nasdaq: GAMB) is a multi-award winning provider of marketing and sports data services looking for exceptional talent interested in the fast-paced, high-growth online gambling industry. The company operates a portfolio of renowned websites and brands – including flagship site Gambling.com and sports betting site Bookies.com as well as iGaming-focused sites Casinos.com, BonusFinder.com and Freebets.com.

Our data ecosystem is evolving rapidly, and we're seeking a talented Data Architect to lead the transformation of our data infrastructure. Join us to build scalable, efficient systems that provide holistic insights into player journeys, financial reporting, and cross-vertical business insights.

Role Overview:

As a Senior Data Architect, you will spearhead the redesign and rebuilding of our data architecture to support the unique demands of business teams. This includes transitioning from manual file-based processes to a modern, automated ETL pipeline, implementing a Medallion architecture (Bronze, Silver, Gold layers) integrated with a Hub-Spoke model for centralized data management and distributed access. You'll work with technologies like Snowflake and Airflow, ensuring seamless data ingestion from diverse sources, including finance, operations, and other business verticals. The goal is to create a unified view of player and operator interactions across multiple sites, enabling advanced analytics, reporting, and decision-making.

Key Responsibilities

• Architecture Redesign: Lead the complete overhaul of our existing data architecture, migrating from manual file handling to a robust, scalable system using Medallion architecture principles for data layering and quality assurance.
• Hub-Spoke Implementation: Design and deploy a Hub-Spoke model to centralize core data assets (e.g., player and operator profiles) while allowing spoke systems for vertical-specific analytics, ensuring data consistency and accessibility.
• ETL Revision: Revamp our ETL processes using Airflow for orchestration, automating data pipelines to handle ingestion from multiple sources, including real-time player activity, operator metrics, and cross-site journeys.
• Data Ingestion and Integration: Build pipelines to ingest data from all business verticals (e.g., finance, marketing, operations), providing comprehensive reporting for finance teams and expanding to support holistic player/operator views.
• iGaming-Specific Focus: Architect solutions centered on player and operator data, tracking journeys across sites, ensuring compliance with industry regulations, and enabling features like personalized recommendations.
• Technology Stack Management: Optimize our use of Snowflake for data warehousing, implementing best practices for performance, security, and cost-efficiency.
• Collaboration and Reporting: You will work withing the Data Engineering team under the Data & Analytics org.  Additionally, you will work closely with finance, business teams to define data models, deliver actionable insights, and support ad-hoc reporting needs.
• Best Practices and Innovation: Enforce data governance, quality controls, documentation and scalability.

Required Qualifications

• Bachelor's or master’s degree in computer science, Data Engineering, or a related field.
• 7+ years of experience in data architecture, with proven expertise in rebuilding large-scale data systems in fast-paced industries like iGaming, fintech, or e-commerce.
• Strong proficiency in Snowflake for data warehousing and modeling.
• Hands-on experience with Airflow or similar ETL orchestration tools.
• Deep understanding of Medallion architecture (Bronze/Silver/Gold layers) and Hub-Spoke models for enterprise data management.
• Expertise in ETL design, data pipeline automation, and handling diverse data sources (structured/unstructured, real-time/batch).
• Strong proficiency in Python and SQL, as these are core to our ETL pipelines and data processing workflows
• Experience with DevOps practices, CI/CD pipelines, and Infrastructure as Code (IaC) tools (e.g., Terraform, GitHub Actions, Jenkins), as the role will involve active contribution to automating and streamlining our daily operations
• Excellent problem-solving skills, with the ability to translate business needs into technical architecture.

Preferred Skills

• Experience with additional tools like DBT for data transformation, Kafka for streaming, or BI platforms (e.g., Tableau, Power BI) for reporting.
• Familiarity with security best practices in data environments (e.g., access controls, encryption, vulnerability scanning)
• Knowledge of iGaming domain, including player lifecycle management, operator integrations, and regulatory considerations.
• Familiarity with cloud environments (e.g., AWS, Azure, GCP) and data lakes.
• Background in building data solutions for multi-site, multi-operator ecosystems.
• Strong communication skills to collaborate with non-technical stakeholders.

Perks & Benefits

• Comprehensive private Healthcare Insurance
• Flexible work environment and home office available
• Home office allowance
• Gym & Leisure Allowance
• All the hardware and software you need to be successful
• Regular company events and social outings, activities, Spot Awards and a Monthly Social Club
• Access to courses for Personal and Career Development
• Company Paid Volunteer Day