Data Engineer

DISQO•Los Angeles, CA

20d•Hybrid

About The Position

DISQOâs mission is to build the worldâs most trusted ad measurement platform that fuels brand growth. The worldâs largest brands, agencies, and media companies trust DISQO for expert insight and AI-driven intelligence about their advertising performance across all platforms. We capture peopleâs sentiments and journeys, connecting them with the brands they value and the media they consume. With this identity-based approach, brands gain more accurate and authentic insight so they can create more meaningful interactions. Joining DISQO Nation means becoming part of a community that champions speed, innovation, and continuous growth. We invest deeply in our talent, empowering our teams to reach their highest potential. Together, we are shaping the future of work at DISQOâdefined by performance, purpose, and impact. We show up each day with curiosity and ambition, committed to learning, accelerating growth, and making a lasting difference. Grounded in our values and principles, we lead and collaborate to elevate performance, accountability, and excellence at every level of the organization. And through it all, we make sure to have fun along the way. 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. Youâll work closely with staff engineers, product managers, and analytics partners in an environment that values ownership, quality, and continuous improvement. Youâll 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 DISQOâs ad measurement platform. Youâll work primarily on batch and near-real-time data processing systems, contributing to analytics-ready datasets used by internal teams and customers. Youâll 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, youâll 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.

Requirements

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

Nice To Haves

Experience with containerization and Docker-based development workflows
Experience with Snowflake or other cloud data warehouses
Exposure to streaming or near-real-time systems (Kafka, Kinesis, etc.)
Experience with data quality, observability, or monitoring tooling
Familiarity with CI/CD pipelines for data platforms
Experience in AdTech or digital advertising platforms

Responsibilities

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