Data Engineer, DISQO

• 3 to 5+ years of experience building and supporting production data pipelines or backend data systems
• Strong proficiency in Scala for data-intensive applications
• Hands-on experience with Apache Spark for batch and streaming data processing
• Experience working in the AWS data ecosystem (for example S3, EMR, Glue, Athena)
• Working knowledge of Kubernetes concepts and experience deploying or operating workloads on Amazon EKS
• Solid understanding of ETL/ELT concepts, data modeling, and advanced SQL
• Experience with workflow orchestration tools such as Airflow or similar
• Familiarity with distributed systems and working with large-scale datasets
• Comfortable working in a Linux-based environment
• Strong collaboration and communication skills in an agile, fast-moving team
• Demonstrated ability to learn new tools and technologies, including AI-powered developer tools for coding and testing

Desirable

• This is a great opportunity to join a high-impact data engineering team building products that directly power how brands measure advertising effectiveness. At DISQO, we use modern cloud infrastructure, scalable data platforms, and pragmatic engineering practices to solve complex, real-world problems at scale
• We are looking for a strong Data Engineer who is hands-on, curious, and eager to grow. You’ll work closely with staff engineers, product managers, and analytics partners in an environment that values ownership, quality, and continuous improvement. You’ll be encouraged to leverage modern tooling, including AI-assisted development tools, to move faster while maintaining high engineering standards
• We believe the best systems are built by small, focused teams that take responsibility for outcomes. We value clean design, data correctness, operational excellence, and thoughtful use of automation to reduce toil and improve developer productivity
• As a Data Engineer, you will design, build, and operate data pipelines and data products that support DISQO’s ad measurement platform. You’ll work primarily on batch and near-real-time data processing systems, contributing to analytics-ready datasets used by internal teams and customers
• You’ll own well-defined components and projects end-to-end, from development through production support, while receiving guidance and technical mentorship from senior engineers
• Over time, you’ll deepen your expertise across distributed data systems, cloud infrastructure, data modeling, containerized workloads, and modern development workflows, including effective use of AI tools to accelerate development and debugging
• Design, build, and maintain scalable, reliable data pipelines using modern big data technologies
• Contribute to core ad measurement data products, including exposure processing, aggregation, and analytics-ready datasets
• Collaborate with Product, Analytics, and Engineering partners to translate business requirements into robust data solutions
• Implement and optimize ETL/ELT workflows with a focus on data correctness, performance, and cost efficiency
• Develop, deploy, and operate data workloads running on Kubernetes, including Amazon EKS
• Write clean, well-structured, and well-tested production code in Scala
• Leverage AI-assisted development tools (for example code generation, refactoring, test creation, and debugging support) responsibly to improve productivity and code quality
• Implement data quality checks, monitoring, and alerting to support operational excellence and meet SLAs
• Participate actively in code reviews, design discussions, and agile ceremonies
• Maintain clear documentation to support data governance, onboarding, and long-term maintainability