Are you ready to revolutionize the advertising industry? At Cognitiv, we are not just another AdTech company—we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting-edge deep learning technology and data science to transform how brands connect with their customers.

Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale. With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry-first ContextGPT product.

As a part of Cognitiv, you will be at the forefront of AI-driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry. Now, we’re growing! The Role This Software Engineer, Big Data is accountable for building and scaling high-performance data systems by developing robust data pipelines and infrastructure, working closely with Data Science, Machine Learning, and Engineering teams to deliver reliable, large-scale data solutions that power analytics and AI-driven initiatives.

This position will be located in Bellevue with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote optional (Thursday/Friday).

What You’Ll Do

Build and scale core data infrastructure. You will design, build, and scale large-scale data ingestion, processing, and warehousing pipelines that support analytics, ML, and activation use cases. Optimize data processing at scale.

You will write and optimize complex SQL and Spark queries to efficiently handle high-volume, distributed datasets. Evolve the data platform. You will contribute to the development and ongoing evolution of our data platform, including systems such as the identity graph and ML feature pipelines.

Ensure system reliability and performance. You will monitor, troubleshoot, and improve highly available data systems to ensure reliability across critical workflows. Partner across technical teams.

You will collaborate cross-functionally with Data Science, Machine Learning, and Product teams to enable and support data-driven initiatives. Improve scalability and efficiency. You will enhance system performance, reliability, and scalability across billions of events and diverse data sources.

Work with modern data technologies. You will use and extend tools such as Spark, Kafka, Iceberg, and cloud-based infrastructure to build robust data solutions.

Who You Are

: Experienced engineer. NET, building production-grade systems. Hands-on big data practitioner.

You have at least 1+ years of experience working directly with Spark or similar technologies in production environments. Cloud-native engineer. You have experience building and operating systems in cloud environments such as AWS, Azure, or GCP.

Strong SQL and data optimization skills. You write and optimize SQL queries to support efficient processing of large-scale datasets. Distributed systems thinker.

You have a solid understanding of distributed systems and how to design for scale, reliability, and performance. Comfortable with large-scale data debugging. You confidently work with large datasets and troubleshoot complex data issues across pipelines and systems.

Collaborative engineering partner. You bring a strong communication style and work effectively across engineering, science, and product teams. Growth-oriented and highly coachable.

You will demonstrate strong learning agility, seek feedback, and continuously improve your technical skills and impact over time.