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Location: Anywhere Senior Build Systems Engineer Remote - Anywhere (American timezones preferred) About Brave Brave is on a mission to protect the human right to privacy online. We’ve built a free web browser that blocks creepy ads and trackers by default, a private search engine with a truly independent index, a browser-native crypto wallet, and a private ad network (opt-in!) that directly rewards you for your attention. And we’re just getting started. Already over 128 million people have switched to Brave for a faster, more private web. Millions more switch every month. The internet is a sea of ads, hackers, and echo chambers. Big Tech makes huge profits off our data, and tells us what’s true and what’s not. Brave is fighting back. Join us! Summary As a colleague (in a team of 8 seniors, each with 15-25+ years of experience) your work will be around reducing toil and building and supporting the automation and processes that enable us to reach 200 million users. We have hundreds of builds running every day for over 1000 GitHub repositories (many open source) with languages like C++, Rust, Go, Python, JavaScript/TypeScript, Ruby, Kotlin, Bash/Shell, HCL and many more. We ship fast and on multiple desktop and mobile platforms, architectures and distribution channels. Multiple CI systems and acceleration/optimization techniques are used to build the right thing and the thing right. Our processes are light and we have no mandatory weekly meetings, 0 on-call, no need to be in an office (unless you really want to) and no strict core hours. Work is autonomous (collaborative at times), asynchronous, flexible. Requirements 10+ years of experience with automation and CI, build and release engineering, testing and reporting tools, code signing, app stores and distribution, packaging (for mobile or desktop apps) extensive and diverse operating system + architecture experience (Android, iOS, Linux, macOS, Windows + x86/x64/arm64) AWS + Terraform any combination of Bash/Shell, Python, Kotlin, Groovy AI-positive but able to code and review generated code privacy and security product mindset, interface with multiple teams, see things end to end, lead on best practices Nice to haves TeamCity (Kotlin DSL), Jenkins (Jenkins Job Builder) browser or Chromium knowledge gn, ninja, siso, reclient, Remote Execution API, EngFlow, ccache/sccache, custom builds systems Gerrit automated testing at scale performance testing and tuning security and quality scanning, SAST/DAST Working at Brave Industry-leader in privacy, with a research and engineering team that’s innovating everyday to keep people safer online and beat Big Tech Highly competitive salaries & benefits, and generous home-office stipends Fully remote team, though we have offices and gatherings in a few locations around the world Welcoming, humble, ridiculously smart teammates, and a truly flat org structure Opportunity to get in early at a hyper-growth company, and revolutionize the web Oh, and did we mention Brendan, our CEO & co-founder, invented JavaScript? Fully remote or hybrid position. No visa sponsorship provided. Check us out brave.com

Location: Warsaw, PL We are looking for a Data Engineer to design, develop, and optimize our data infrastructure on Databricks. You will architect scalable pipelines using BigQuery, Google Cloud Storage, Apache Airflow, dbt, Dataflow, and Pub/Sub, ensuring high availability and performance across our ETL/ELT processes. You will leverage Great Expectations to enforce data quality standards. The role also involves building our Data Mart (Data Mach) environment and implementing CI/CD best practices. A successful candidate has extensive knowledge of cloud-native data solutions, strong proficiency with ETL/ELT frameworks (including dbt), and a passion for building robust, cost-effective pipelines. Responsibilities Data Architecture & Strategy – Define and implement the overall data architecture on GCP, including data warehousing in BigQuery/Databricks, data lake patterns in Google Cloud Storage, and Data Mart (Data Mach) solutions. Integrate Terraform for Infrastructure as Code to provision and manage cloud resources efficiently. Establish both batch and real-time data processing frameworks to ensure reliability, scalability, and cost efficiency. Pipeline Development & Orchestration – Design, build, and optimize ETL/ELT pipelines using Apache Airflow for workflow orchestration. Implement dbt (Data Build Tool) transformations to maintain version-controlled data models in BigQuery, ensuring consistency and reliability across the data pipeline. Use Google Dataflow (based on Apache Beam) and Pub/Sub for large-scale streaming/batch data processing and ingestion. Automate job scheduling and data transformations to deliver timely insights for analytics, machine learning, and reporting. Event-Driven & Microservices Architecture – Implement event-driven or asynchronous data workflows between microservices. Employ Docker and Kubernetes (K8s) for containerization and orchestration, enabling flexible and efficient microservices-based data workflows. Implement CI/CD pipelines for streamlined development, testing, and deployment of data engineering components. Data Quality, Governance & Security – Enforce data quality standards using Great Expectations or similar frameworks, defining and validating expectations for critical datasets. Define and uphold metadata management, data lineage, and auditing standards to ensure trustworthy datasets. Implement security best practices, including encryption at rest and in transit, Identity and Access Management (IAM), and compliance with GDPR or CCPA where applicable. Scientists & Analytics Enablement – Collaborate with Data Science, Analytics, and Product teams to ensure the data infrastructure supports advanced analytics, including machine learning initiatives. Maintain Data Mart (Data Mach) environments that cater to specific business domains, optimizing access and performance for key stakeholders. Requirements 1. Experience – 3+ years of professional experience in data engineering, with at least 1 year in mobile data 2. Technical Expertise with GCP Stack – Proven track record building and maintaining BigQuery environments and Google Cloud Storage based data lakes. – Deep knowledge of Apache Airflow for scheduling/orchestration and ETL/ELT design. – Experience implementing dbt for data transformations, RabbitMQ for event-driven workflows, and Pub/Sub + Dataflow for streaming/batch data pipelines. – Familiarity with designing and implementing Data Mart (Data Mach) solutions, as well as using Terraform for IaC. 3. Programming & Containerization – Strong coding capabilities in Python, Java, or Scala, plus scripting for automation. – Experience with Docker and Kubernetes (K8s) for containerizing data-related services. – Hands-on with CI/CD pipelines and DevOps tools (e.g., Terraform, Ansible, Jenkins, GitLab CI) to manage infrastructure and deployments. 4. Data Quality & Governance – Proficiency in Great Expectations (or similar) to define and enforce data quality standards. – Expertise in designing systems for data lineage, metadata management, and compliance (GDPR, CCPA). – Strong understanding of OLTP (Online Transaction Processing) and OLAP (Online Analytical Processing) systems. 5. Communication – Excellent communication skills for both technical and non-technical audiences. – High level of organization, self-motivation, and problem-solving aptitude. What we offer Competitive compensation based on your experience and expertise Long-term contract-based collaboration A collaborative and open environment Flexible collaboration arrangements