Enterprise Solution Architect (Life Sciences & Data Modernization)

Intuition IT Solutions Ltd

Macclesfield, UK

4 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Compensation

£80,000.0

Working hours

Regular working hours

Job source

www.careerboard.com

Tech stack

Java (Programming Language) Artificial Intelligence Airflow Amazon Web Services Amazon S3 Microsoft Azure Big Data Clinical Data Repository Cloud Computing Cloud Engineering Code Review Computer Programming

+18 more

Data Infrastructure Data Transformation Graph Database Python (Programming Language) Neo4j Scala (Programming Language) Shell Script Software Engineering SQL Databases Google Cloud Apache Spark Pyspark Kubernetes Terraform Docker Jenkins Databricks Microservices

Job description

We are seeking a seasoned Enterprise Solution Architect with deep expertise in the Life Sciences value chain and data modernization to lead complex, high-value client engagements. You will serve as a strategic bridge between business objectives and technical execution, driving architectural governance, solution shaping, and technical sales enablement, specifically within the Life Sciences sector., * Life Sciences Domain Leadership: Drive end-to-end data modernization across the Life Sciences value chain-spanning R&D, Clinical Data, and Commercial operations. Lead discovery workshops to define high-impact use cases that accelerate drug development and commercial outcomes.

Solution Strategy & Shaping: Translate complex business problems into scalable, value-led architecture roadmaps across AWS, Azure, and GCP. Lead end-to-end solutioning for high-value pursuits.
Architecture Leadership: Provide technical governance for critical programs. Drive the adoption of modern data platforms, including Lakehouse architectures for large-scale clinical and commercial data sets.
Innovation & GenAI: Spearhead the development of GenAI assets (eg, agentic workflows for R&D/IT) and Proof-of-Concepts (POCs) tailored to Life Sciences workflows.
Stakeholder Management: Partner with C-suite and senior stakeholders to align technical roadmaps with enterprise goals, ensuring compliance and data reusability across global research and commercial organizations.
Technical Enablement: Establish best practices for the Life Sciences Center of Excellence (COE), mentor technical teams, and perform rigorous code reviews.

Requirements

Experience: 20+ years of experience across architecture, application development, and big data analytics, with significant tenure in the Life Sciences industry.
Domain Expertise: Proven track record in Life Sciences, specifically in Clinical Data, R&D, and Commercial Analytics. Deep understanding of the data challenges inherent in the Life Sciences value chain.
Core Architecture: Expertise in Data Modernization, Microservices, Cloud Architecture, and Lakehouse patterns.
Data & AI: Deep hands-on proficiency in Databricks (Spark, PySpark, DLT), GenAI (Agent Core, Copilot Studio, Amazon Bedrock), and Graph Databases (Neo4j).
Cloud & Tools: Strong command of AWS (Lambda, Glue, EMR, MWAA, S3), Azure, Airflow, Terraform, Docker, Kubernetes, and Jenkins.
Programming: Advanced skills in Python, SQL, Scala, Java, and Shell Scripting.

Leadership Competencies

Strategic Advisory: Proven ability to lead post-technical win strategies and define long-term platform adoption roadmaps for enterprise-level Life Sciences programs.
Delivery Ownership: End-to-end accountability for complex architectural solutions, ensuring successful production go-lives in regulated environments.
Technical Enthusiasm: A continuous learner, proactive in navigating new product innovations and bridging the gap between Life Sciences business priorities and engineering feasibility.