Software Engineer, Big Data

Cognitiv•Bellevue, WA

6h•Hybrid

About The Position

At Cognitiv, 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 is to bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale. Our innovative platform offers advertisers unprecedented flexibility. 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. We are growing and looking for a Software Engineer, Big Data to build and scale high-performance data systems by developing robust data pipelines and infrastructure. You will work 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).

Requirements

4+ years of experience working with a managed language such as Java or .NET, building production-grade systems.
At least 1+ years of experience working directly with Spark or similar technologies in production environments.
Experience building and operating systems in cloud environments such as AWS, Azure, or GCP.
Strong SQL and data optimization skills, including writing and optimizing SQL queries to support efficient processing of large-scale datasets.
Solid understanding of distributed systems and how to design for scale, reliability, and performance.
Comfortable working with large datasets and troubleshooting complex data issues across pipelines and systems.
Strong communication style and ability to work effectively across engineering, science, and product teams.
Strong learning agility, seeking feedback, and continuously improving technical skills and impact over time.

Nice To Haves

Experience scaling large datasets using SQL and Spark
Background working with high-volume, real-time data systems
Experience operating and maintaining highly-available systems
Proficiency in Python
Familiarity with tools such as Kafka, ClickHouse, or AWS EMR/S3

Responsibilities

Build and scale core data infrastructure, including designing, building, and scaling large-scale data ingestion, processing, and warehousing pipelines that support analytics, ML, and activation use cases.
Optimize data processing at scale by writing and optimizing complex SQL and Spark queries to efficiently handle high-volume, distributed datasets.
Evolve the data platform by contributing 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 by monitoring, troubleshooting, and improving highly available data systems to ensure reliability across critical workflows.
Partner across technical teams by collaborating cross-functionally with Data Science, Machine Learning, and Product teams to enable and support data-driven initiatives.
Improve scalability and efficiency by enhancing system performance, reliability, and scalability across billions of events and diverse data sources.
Work with modern data technologies, using and extending tools such as Spark, Kafka, Iceberg, and cloud-based infrastructure to build robust data solutions.