About the job
Join our innovative Data Solutions team, where we're developing the core intelligence platform relied upon by prominent public and private sector organizations to investigate threats, monitor risks in real-time, and extract valuable insights from blockchain and related data on a large scale. We prioritize agility and efficiency, seeking engineers who are eager to take ownership, thrive in a fast-paced environment, and are motivated by the mission requirements of our clients to deliver significant real-world impact.
In this position, you will:
Design and spearhead the development of new platform features that support critical investigations and monitoring processes.
Manage services that handle the ingestion, transformation, and delivery of hundreds of terabytes of data, ensuring service-level objectives (SLOs) for latency, freshness, and availability are met.
Enhance the scalability, performance, and cost-effectiveness of our data plane and APIs.
Elevate quality standards across reliability, security, and compliance for both cloud and on-premises setups.
Mentor engineers across various teams and influence the technical strategy beyond your immediate group.
Own and improve backend services that drive customer-facing APIs, usage and billing systems, alerting, and data observability.
Lead both team and cross-team initiatives from start to finish: discovery, architecture, implementation, rollout, and post-launch analysis.
Design event-driven and streaming workflows (e.g., Kafka) with robust data contracts and schema evolution.
Promote operational excellence through SLOs, runbooks, on-call duties, incident reviews, and capacity planning for high-query-per-second systems.
Collaborate with product, data engineering/science, and security teams to translate customer needs into sustainable systems.
We seek candidates who possess:
Extensive backend engineering experience in building cloud-hosted services and data pipelines, preferably on AWS or GCP (experience with both is a plus).
Strong expertise in APIs, streaming systems, and distributed systems (e.g., microservices on Kubernetes).
Proven track record of managing systems at scale (hundreds to thousands of requests per second; terabyte to petabyte data volumes).
High level of judgment regarding reliability, security, and cost management, demonstrating measurable improvements.
Capability to lead through influence—mentoring, conducting design reviews, and collaborating across teams.

