Solution Architect (US) en Lynx Analytics

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.

 

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.

 

•    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, Typescript, 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.

 

•    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.

 

•    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