Role Description Design, develop, and maintain scalable ELT pipelines and modern data architectures. - Build and optimize data transformation workflows using dbt and SQL. - Collaborate closely with software engineers and product teams to support data-driven applications. - Develop infrastructure as code using Terraform. - Support web application integrations involving Node.js, TypeScript, GraphQL, and React. - Improve data reliability, monitoring, and operational excellence across the platform. - Participate in production support through an on-call rotation (1 week every 4 weeks) and serve as backup on-call engineer for an additional week every 4 weeks. - Collaborate with US-based engineering teams to troubleshoot production issues and continuously improve platform performance. - Contribute to best practices around data engineering, automation, and cloud architecture. Qualifications - Strong experience building ELT pipelines and modern data engineering solutions. - Advanced experience with dbt and SQL. - Hands-on experience with Terraform. - Experience working with web application technologies, including: Node.js, TypeScript, GraphQL, React. - Strong analytical and problem-solving skills. - Experience working in Agile environments. - Excellent communication skills and ability to collaborate with distributed international teams. - English proficiency sufficient to work daily with US-based engineers. Requirements - Nice to have: Snowflake. - AWS. - Apache Airflow. - Looker. - Python. - GitHub. - Experience supporting production environments and participating in on-call rotations. - Experience designing modern cloud-native data platforms. - English level: Upper-Intermediate. Benefits - International projects. - In-office, hybrid, or remote flexibility. - Medical healthcare. - Recognition program. - Ongoing learning & reimbursement. - Well-being program. - Team events & local benefits. - Sports compensation. - Referral bonuses. - Top-tier equipment provision.

• Design, develop, and maintain scalable ETL/ELT pipelines using Databricks and Python. • Build, test, and support integrations between Databricks, Oracle, and downstream systems. • Develop and maintain high-quality data extracts for internal and external stakeholders. • Own and document inbound and outbound data feeds. • Monitor data pipelines for performance, reliability, and quality; identify and resolve issues. • Design and optimize data models supporting operational, analytical, and financial reporting. • Contribute to continuous improvement of the data platform using industry best practices. • Partner with technical and business stakeholders to gather requirements and deliver solutions. • Support internal applications and ensure business continuity. • Collaborate effectively across engineering and cross-functional teams.

Role Description We are looking for a highly technical, hands-on Senior Data Engineer to drive the evolution of our data delivery platform while leading a team of data engineers. This is a player-coach role: - Architect our next-generation data stack. - Build proofs-of-concept (POCs) and prove out new technologies before committing to them at scale. - Manage and grow a team of engineers who report directly to you. - Partner closely with engineering leadership to shape the technical direction of our pipelines while staying hands-on in the systems. We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. We expect our engineers to work in a modern, AI-assisted way: - Use AI coding tools and prompt-based workflows to move faster without compromising quality. - Evaluate tools, build POCs, and make pragmatic, evidence-based decisions about what we adopt next. This is a build-and-prove role: - Write code, design schemas, profile queries, and understand the "how" and "why" behind every pipeline. - Mentor your team to do the same. - Team Leadership & People Management: Lead, manage, and grow a distributed team of data engineers (across North America and India). - AI-Assisted Development: Champion the use of AI coding assistants and prompt-based development. - Hands-On POCs & Prototyping: Build proofs-of-concept to validate new tools and patterns. - Tech Stack Strategy & Architecture: Help shape the technical vision for our ETL and data platform. - Platform Modernization: Drive the migration away from Azure Databricks toward a more open, flexible stack. - Build & Own Pipelines: Design, build, and optimize robust ETL pipelines. - Deep System Integration: Master all systems upstream and downstream to ensure seamless data delivery. - Operational Excellence: Establish testing frameworks, QA plans, observability, and CI/CD practices. - Technical Leadership Through Influence: Set technical standards and raise the bar across a distributed team. - Domain Mastery: Rapidly learn the nuances of the Advertising and Market Research domain. Qualifications - 8+ years in data engineering / ETL, with a strong track record as a hands-on engineer. - Hands-on experience using AI coding tools and strong prompt-based development skills. - Expert-level SQL and RDBMS skills with deep experience in SQL Server and Postgres. - Hands-on experience with technologies such as ClickHouse, dbt, and open-source data pipeline tools. - Strong, hands-on AWS experience. - Demonstrated ability to independently prototype, benchmark, and evaluate new technologies. - Strong proficiency in Python (or similar) for building and automating data pipelines. - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Requirements - Previous experience in Advertising, Media, or Market Research (Bonus Points). - Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code (Bonus Points). - Experience with streaming/real-time data technologies (e.g., Kafka) (Bonus Points). Benefits - Medical, Dental & Vision Insurance - 401k with Company Match - Flexible PTO - Commuter Benefits - Gym Discounts - Summer Fridays

• Serve as a primary responder for production data incidents, quickly diagnosing root causes, implementing fixes, and ensuring data integrity. • Design, implement, and maintain monitoring, logging, and alerting systems for all production data pipelines and infrastructure. • Manage, deploy, and maintain data and integrations pipelines and APIs. • Continuously identify and implement optimizations to improve the speed, scalability, and efficiency of data processing jobs and API performance. • Develop and enforce data validation and quality checks within the pipelines to minimize errors and inconsistencies in production data. • Collaborate with DevOps teams on managing the underlying infrastructure (AWS components) that hosts the data platform. • Maintain comprehensive and up-to-date documentation for all operational procedures, pipeline architectures, and troubleshooting runbooks. • Communicate incident status and SLA reports to management. • Develop & deploy data pipelines, backend ingestion or integration jobs to support minor enhancements and bug fixes. • Work with data from a variety of sources including but not limited to: CRM data, Product data, Marketing data, Order flow data, Support ticket volume data, Finance data etc. • Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new offices.