Calliere Group

• Process and analyze genomic and other omics datasets (for example, whole‑genome, whole‑exome, RNA‑seq, or similar assays), including alignment, quality assessment, variant detection, and annotation. • Develop, document, and maintain reproducible analysis pipelines using modern workflow or pipeline tools and scripting languages. • Implement best practices for data quality control, including monitoring run performance, detecting technical issues, and proposing corrective actions. • Integrate data from multiple sources, harmonize formats and metadata, and prepare analysis‑ready datasets. • Work with common bioinformatics tools and file formats (e.g., FASTQ, BAM/CRAM, VCF, BED, GFF/GTF) in a Unix/Linux environment. • Develop and execute exploratory analyses, including cohort‑level summaries, visualization of key metrics, and interpretation of variant and gene‑level results. • Prepare clear, well‑structured reports, figures, and presentation materials describing methods, assumptions, and findings for collaborators with diverse backgrounds. • Contribute to the evaluation and adoption of new algorithms, tools, and workflows in bioinformatics and data analysis. • Collaborate with other team members on study design, analysis plans, timelines, and prioritization of tasks.

• Guide and mentor a senior team, with real investment in their growth, performance, and long-term trajectory. • Define where bioinformatics is going and how it supports broader product and scientific goals. • Partner closely with product and engineering leaders to ensure the work being done actually moves the needle. • Represent the function at the leadership level—clearly communicating priorities, tradeoffs, and where investment is needed. • Bring structure to how projects are planned, executed, and tracked so things scale without chaos. • Work cross-functionally to translate biological insight into usable, production-grade tools. • Play a key role in hiring and shaping the team as it grows. • Keep the team aligned with evolving tools, standards, and best practices in the genomics space.

• Join a small, senior team at the early stages of building a product from scratch • Convert product requirements into thorough technical design documentation • Architect and implement backend services built to handle enterprise-scale demand • Design systems with high availability and fault tolerance in mind • Embed security thinking at every layer — application, API, and infrastructure • Own API design across both public-facing and internal service boundaries, including schema modeling and integration patterns • Work cross-functionally with product and design stakeholders throughout the development lifecycle • Thrive in a remote-first environment using a blend of synchronous video calls and async communication • Stay current with emerging technologies and approach new challenges with genuine curiosity • Take part in engineering hiring by conducting interviews and evaluating candidates

• Design, implement, and maintain highly scalable, fault-tolerant backend services powering real-time data synchronization and streaming • Optimize systems for latency, throughput, and reliability to support demanding data transfer workflows • Guide architectural decisions around multi-region deployment, disaster recovery, and data residency for customers operating worldwide • Collaborate with both engineering and product stakeholders to deliver practical solutions that directly benefit end users and business needs • Own projects from concept to production—work with internal and external users to understand requirements and troubleshoot real-world scaling problems • Continuously monitor, evaluate, and improve platform automation, observability, and incident response techniques

• Architect and implement systems that collect, store, and surface insights from large-scale creative and performance datasets. • Build robust APIs empowering clients, dashboards, and data consumers across the company. • Improve how marketers visualize and act on creative data through unified, reliable backend systems. • Diagnose and solve performance bottlenecks, infrastructure challenges, and integration issues. • Collaborate with a talented team to evolve architecture, tooling, and development processes as we grow.

• Shape and scale our real-time data streaming systems — the backbone powering billions of in-the-moment decisions across our platform. • Architect and improve services that process millions of events per second with single‑digit millisecond latency, touching almost every part of our data plane. • Tackle challenges few companies face: ultra‑low‑latency ingestion, distributed caching, deduplication at scale, and fault‑tolerant event computation. • Be the type of engineer who gets excited by raw throughput charts translating into better customer outcomes.