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SUMMARY STATEMENT
We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will define data models, system architecture, and integration patterns, and validate those designs hands-on - building prototypes, proofs of concept, and early pipeline or application components to de-risk decisions before a full delivery team builds on them. This is an architecture-first role: data and software engineering work you do is in service of setting technical direction and unblocking delivery teams, not sustained production-scale build.
KEY RESPONSIBILITIES
Solution Architecture
•   Own solution architecture for client engagements: data models, system design, integration patterns, and technology choices, translated into designs delivery teams can build from.
•   Lead technical discovery with clients: understand requirements, assess existing systems, and present architectural options and trade-offs to technical and non-technical stakeholders.
•   Define standards, reusable patterns, and reference architectures that other engineers at Lynx can build on across engagements.
•   Make pragmatic trade-offs between build speed, cost, scalability, and maintainability, and clearly explain the reasoning behind them.
•   Review technical designs and key implementation decisions from delivery teams to ensure they stay aligned with the intended architecture.
Hands-On Validation & Enablement
•   Validate architectural decisions hands-on - building prototypes, proofs of concept, and early data pipeline or application components to test feasibility before full-scale build.
•   Partner with data engineers and software engineers to unblock them on ambiguous technical problems, then hand off cleanly once the direction is proven.
•   Set up early evaluation, testing, or monitoring approaches so delivery teams inherit a working foundation, not just a diagram.
•   Contribute to internal tooling, accelerators, and knowledge-sharing that raise the technical bar across the practice.
SKILLS, QUALIFICATIONS AND EXPERIENCE
•   Bachelor's degree in Computer Science, Engineering, or a related field.
•   5-8+ years of experience spanning data engineering and software engineering, with demonstrated experience moving into solution or systems architecture.
•   Track record of designing data models, system architectures, and integration patterns for production systems, not just diagramming them.
•   Hands-on proficiency in at least one modern language (e.g., Python, Java, or similar) and comfort prototyping pipeline or application components personally.
•   Solid grounding in data engineering fundamentals (pipeline design, data modeling, ETL/ELT) and software engineering fundamentals (API design, testing, CI/CD).
•   Experience working in a consulting or client-facing environment - comfortable leading discovery conversations, presenting trade-offs, and managing ambiguity.
•   Experience with cloud platforms (AWS, GCP, or Azure) is a plus.
•   Experience working within a consulting or professional services firm is a plus.
KEY COMPETENCIES
•   Architectural Judgment: Balances build speed, cost, scalability, and maintainability, and knows when to prototype personally versus hand off to a data or software engineer.
•   Stakeholder Mentality: Treats the company's and client's goals as their own and is genuinely motivated by delivery success.
•   Technical Communication: Translates complex architectural decisions clearly for both engineers and non-technical business stakeholders.
•   Discretion & Integrity: Handles sensitive client and technical information with professionalism and sound judgement.
•   Problem Solving: Approaches ambiguous technical challenges proactively and with a solution-oriented mindset, taking initiative rather than waiting to be directed.
•   Collaboration: A team player who builds strong working relationships with delivery teams and communicates effectively across all levels.
WHY YOU WILL LOVE IT HERE
•   A collaborative and global culture that values real outcomes
•   High ownership, zero micromanagement
•   Rapid learning opportunities and diverse challenges
•   Flat organisational hierarchy with high visibility and accessibility to our leaders
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