Cygnus Professionals IncSolid experience designing and consuming REST APIs, including integration with other services/platforms
Experience working with complex, data‑driven applications (analytics, simulators, optimization / decision‑support systems)
Ability to work confidently with an existing codebase: understand it, extend it, stabilize it
Comfortable collaborating with Data Science teams and translating modelling / optimization logic into backend services
Familiarity with cloud‑based (AWS) production environments with an understanding of how backend services are deployed and operated in production
Experience with standard engineering best practices (error handling, logging, performance awareness)
Basic DevOps awareness (working with existing CI/CD pipelines, deployment processes, and production diagnostics - no infrastructure ownership expected)
Ability to document and formalize understanding of the system (e.g. high‑level flows, integrations, dependencies)
Independent working style, clear communication, proactive escalation of risks or blockers
Pharma or commercial analytics context
Proven experience acting as a hands‑on technical lead (not coordination/guidance‑only):
driving technical decisions,
connecting backend, frontend, and data/optimization layers,
unblocking teams when requirements are incomplete or evolving
Solid understanding of system integrations and end‑to‑end flows (UI → backend → optimization / DS → platform dependencies)
Comfortable collaborating with Data Science teams and translating modelling / optimization logic into backend services
Ability to apply engineering best practices (pragmatically and consistently)
Strong understanding of cloud‑based application architectures (AWS)
Ability to work effectively with existing DevOps and CI/CD setups: understanding deployment flows, environment differences, and production constraints
Production‑minded engineering approach: designing solutions with operability, monitoring, and maintainability in mind
Strong communication skills, including the ability to clearly write down and explain technical decisions
Ability and habit to produce lightweight but durable artefacts such as:
system or integration diagrams,
high‑level architecture views,
key decision rationales,
deployment context,
onboarding references
Clear mindset of leaving the system stronger and easier to maintain than before
Pharma or commercial analytics context
GitHub engineering practices (PRs, branching, Actions)
Testing + CI/CD mindset (unit/integration tests, automated checks)
Config-driven scalable architecture (reusable components, toolkit/SDK software development)
Strong documentation + cross-team collaboration skills
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