Software Engineer, Big Data

• →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.

• 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.

• 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

• 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

• 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

• 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

• 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.