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. 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.
Bonus Points If You Have:
- 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
What success looks like in your first 30 days:
- Ramp quickly on our data platform, tools, and architecture
- Build strong context on existing pipelines, systems, and key challenges
- Establish relationships with team members and cross-functional partners
- Begin contributing to small improvements or bug fixes
What success looks like in your first 60 days:
- Independently own components of data pipelines or infrastructure
- Deliver measurable improvements in performance, reliability, or scalability
- Align with stakeholders on priorities and technical direction
- Start contributing to design discussions and technical decisions
What success looks like in your first 90 days:
- Fully own key parts of the data platform or pipeline ecosystem
- Deliver measurable business impact through improved data systems
- Drive improvements to at least one core system or process
- Operate autonomously and act as a trusted partner across teams
Salary: $130,000 - $170,000 USD Base Salary + Equity
- Medical, dental & vision coverage (some plans 100% employer-paid)
- 12 weeks paid parental leave + 4 weeks WFH
- Unlimited PTO + Work-From-Anywhere August
- Career development with clear advancement paths
- Equity for all employees
- Hybrid work model & daily team lunch
- Health & wellness stipend + cell phone reimbursement
- 401(k) with employer match
- Parking (CA & WA offices) & pre-tax commuter benefits
- Employee Assistance Program
- Comprehensive onboarding (Cognitiv University)
- …and more!
- Festiv – We make work fun with cross-team games, events, and creative team bonding.
- Responsiv – You’ll be close to clients and leadership, influencing real outcomes.
- Inclusiv – Diversity and individuality are celebrated across all levels.
- Inventiv – We reward curiosity and embrace bold ideas.
- Transformativ – We support your growth with training, mentorship, and flexibility.
- Collaborativ – We operate across coasts, connected by purpose and teamwork.
Skills Required
- 4+ years of experience working with a managed language like Java or .NET
- 1+ years of experience with Spark or similar technologies in production environments
- Experience in cloud environments like AWS, Azure, or GCP
- Strong SQL and data optimization skills
- Solid understanding of distributed systems design
What We Do
Cognitiv is a deep learning advertising company redefining how brands connect with consumers. Since 2015, we have built a custom AI platform that predicts consumer behavior in real time and drives performance at scale. Advertisers can activate through their preferred DSP, our managed service DSP, or our industry-first ContextGPT product. By combining advanced data science with flexible activation, we deliver precision, relevance, and measurable impact across channels.
Why Work With Us
At Cognitiv, you will work on real-world AI that directly shapes media performance. We are profitable, growing, and deeply technical, with close access to leadership and clients. We value curiosity, collaboration, and ownership, and we invest in your growth through equity, flexibility, and clear career paths.








.png)