Data Modernisation Architect - Job Specification
Grade – Manager or Senior Manager
Location: Manchester
Position Overview
We are seeking an experienced Data Modernisation Architect to lead AI ready transformative data platform initiatives for our clients across Life Sciences, Consumer Products, Retail, and Energy sectors. This role combines deep technical expertise in modern cloud AI and data platforms with the ability to translate complex technical solutions into compelling business narratives for C-suite stakeholders.
Key Responsibilities
Technical Leadership
- Design and architect end-to-end data modernisation solutions leveraging Databricks and/or Snowflake platforms
- Lead the assessment of legacy data architectures and develop comprehensive modernisation roadmaps including definition of data lakehouse architectures, medallion architecture patterns, and modern data governance frameworks
- Architect scalable ETL/ELT pipelines, real-time streaming solutions, and advanced analytics capabilities
- Establish best practices for DataOps, data quality management, and platform optimization
- Provide technical guidance on cloud infrastructure (Azure, AWS, or GCP) integration with data platforms
- Apply deep understanding of industry-specific data challenges in Life Sciences, Consumer Products, Retail, or Energy sectors
- Design solutions addressing regulatory requirements (e.g., GxP for Life Sciences, GDPR, data sovereignty)
- Develop industry-specific use cases including supply chain optimization, customer analytics, commercial effectiveness, or operational intelligence
- Architect solutions supporting domain-specific needs such as clinical trial data, product lifecycle management, omnichannel retail, or energy trading and distribution
- Develop compelling data visualisations and storytelling frameworks to illustrate transformation impact
- Contribute to proposals, statements of work, and client presentations
- Support business development activities through thought leadership and technical expertise
- Lead workshops and discovery sessions to understand business objectives and technical requirements and create presentations and business cases demonstrating ROI and strategic value
- Navigate complex stakeholder landscapes and drive consensus across technical and business functions
- Mentor junior team members on technical skills and client management including contribution to internal capability building and knowledge sharing initiatives
Required Qualifications
- Essential: 8+ years of hands-on experience with Databricks and/or Snowflake in enterprise environments
- Deep expertise in modern data architecture patterns (data lakehouse, data mesh, event-driven architectures)
- Essential: 2+ years of experience in at least one target industry: Life Sciences, Consumer Products, Retail, or Energy
- Understanding of industry-specific data ecosystems, regulations, and business processes
- Familiarity with relevant domain concepts (e.g., clinical data standards, supply chain systems, customer data platforms, energy trading systems)
- Proven track record delivering data transformation projects in consulting or client-facing roles
- Demonstrated ability to manage senior stakeholder relationships and influence decision-making
- Experience leading workshops, requirements gathering, and solution design sessions
- Strong commercial acumen with experience contributing to proposals and business development
- Exceptional ability to communicate complex technical concepts to non-technical audiences
- Proven track record creating compelling presentations and executive-level documentation
Preferred Qualifications
- Databricks Certified Data Engineer or Solution Architect certification
- SnowPro Core or Advanced certification
- Big 4 or tier-1 consulting firm experience
Personal Attributes
- Strategic thinker with strong problem-solving capabilities
- Self-starter who can work independently and manage ambiguity
- Collaborative team player with strong interpersonal skills
- Adaptable and comfortable working in fast-paced, dynamic environments
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