Software Engineer, Big Data

Cognitiv•Bellevue, WA

7h•Hybrid

About The Position

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).

Requirements

Experienced engineer. You bring 4+ years of experience working with a managed language such as Java or .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.

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. 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.