Observability Specialist
How you'll help us achieve it
Wave is now the largest financial institution in Senegal and Côte d'Ivoire, with millions of users, growing rapidly year-on-year. And, we’re still in the early days of our product roadmap and potential impact on people’s everyday lives.
As an Observability Engineer at Wave, you will help engineers understand, operate, debug, and improve the systems that power payments for millions of users across Africa.
You will own and evolve Wave’s observability platform across our Python backend, GraphQL API, Postgres and CockroachDB databases, Kubernetes workloads, cloud infrastructure, and on-premises environments. Your work will make it easier for product, database, infrastructure, and security teams to detect problems and regressions early, understand system behaviour, resolve incidents quickly, and make well-informed reliability and performance decisions.
You'll work in the newly formed Performance & Observability team and report to the Director of Platform. You'll partner closely with infrastructure, database, and product engineering teams to improve how we instrument our services.
In this role you'll:
Improve our understanding of production behaviour across application code, GraphQL APIs, databases, caches, Kubernetes workloads, cloud infrastructure, async jobs, and on-premises environments.
Partner with product and platform teams to define meaningful service-level indicators, reduce alert fatigue, and ensure alerts are actionable, reliable, and tied to user impact.
Build internal tooling and self-service workflows that help engineers instrument services, investigate incidents, analyse performance, and understand dependencies.
Help teams identify reliability, latency, capacity, and cost issues before they become user-facing incidents.
Establish and implement observability standards, documentation, and training materials that scale across Wave’s engineering organisation.
Operate and improve our observability platform (e.g., Datadog, Honeycomb, Prometheus, Grafana, OpenTelemetry) while controlling costs as data volume grows.
You might be a good fit if you...
Care a lot about working on software whose mission you can believe in.
Have a bias for action. You see a problem, you fix a problem. You get buy-in for your solutions and keep work moving.
Approach your work with a growth mindset and use your skills and experience to mentor less-experienced engineers.
Are excited to build world-class infrastructure that powers economic opportunity for an entire continent.
Requirements
5+ years of experience in observability, SRE, platform engineering, infrastructure engineering, backend engineering, or production systems engineering.
Deep understanding of metrics, logging, tracing, profiling, alerting, dashboards, service-level indicators, and incident response workflows at scale.
Experience building internal tools, libraries, automation, or platforms used by other engineers.
Excellent communication and collaboration skills. This role succeeds by helping other engineers build, operate, and debug better systems.
Pragmatic judgment about when to improve tooling, when to simplify, and when to avoid unnecessary complexity.
Experience learning, analyzing, and working on other people’s code.
Technical Skills
Proficiency in at least one backend language, preferably Python.
Experience with observability tools such as Prometheus, Grafana, Datadog, OpenTelemetry, Jaeger, Tempo, Loki, Honeycomb, Sentry, or similar systems.
Experience with at least some our stack, Postgres, CockroachDB, Redis, GraphQL, or Kubernetes.
Experience with OpenTelemetry instrumentation and collector configuration at scale
About the Performance & Observability Team
The Performance and Observability team was recently formed with the hiring of our first performance engineer, and is expanding with this Observability position. The team is and will continue to define its scope. The observability scope within the team currently is:
Ownership, management and evolution of observability tools: Datadog, Honeycomb, Sentry, and Pyroscope.
Design of SLOs and support product teams in implementing them.
Support all teams in improving their alert quality.
Ownership of observability modules and code, ensuring consistent naming conventions across all our systems.
Some recent and potential projects, as examples of specific things the team has worked on:
Early detection of regressions in our code. This could be a performance, reliability, or other regression that impacts our users.
CPU profiling in production.
SLO support for product teams.
Scaling our Observability platform to support 4x our current volume while keeping costs in check.
About engineering at Wave
We care about the big picture. We don’t hire engineers to just ship tickets. We hire them to solve problems. That means caring deeply about outcomes, understanding context, and jumping in wherever something’s broken, even if it’s technically “not your area.” When we see problems, inefficiencies, or opportunities to make something better, we act. We dig into operational issues, clarify fuzzy product specs, or step into unfamiliar code to help unblock teammates.
We move as fast as possible. Speed matters. It lets us try things quickly, get feedback early, and course-correct while it’s cheap. So we write small PRs. We aim for MVPs. We leave TODOs and file follow-ups. We don’t over-perfect v1. That said, we’re building a financial product. Some things—like money movement, correctness, or security—deserve more caution.
We like boring technology. We favor tools that are reliable, well-understood, and easy to debug. This keeps us focused on solving meaningful problems instead of wrestling with unpredictable infrastructure. If a new technology helps us move faster, build safer, or solve a real need, we’ll consider it. But we don’t adopt tools just because they’re new—we adopt them because they’re right.
Simplicity is a strategy. It lets us focus our energy where it matters most: serving our users.
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