Job Description

About Movar

 At Movar, we understand that project delivery is getting increasingly complex. Since 2013, we’ve been helping companies of all sizes improve the way projects are delivered.

Our mission is to be the number one provider of innovative project solutions, driven by a community of experienced, caring, and passionate project professionals—all seeking to improve the way projects are delivered.

Our vision is simple yet powerful: to improve the lives of people everywhere through the delivery of projects. We provide tailored services ranging from organisational systems implementation to project transformation and complete programme recovery.

We’re proud to have been named Winners of the Global Project Controls Innovation of the Year Award 2024.

Why Join Movar?

 Movar is in an exciting period of growth, and there’s never been a better time to be part of our journey. We’re building something special—scaling our business while staying true to our people-first approach.

At Movar, we invest in our teams, fostering an environment where development is valued and individuals are encouraged to grow with the company. Our unique culture sets us apart from other consulting practices, and we’re keen to build a team that is as ambitious as we are.

Our IDEAL Values:

• Integrity – We do the right thing, always.
• Drive – We push boundaries and strive for excellence.
• Empathy – We care deeply about our people and clients.
• Adaptability – We embrace change and thrive in it.
• Loyalty – We stand by each other and our mission.

Job Summary

 About the Role 

Movar is seeking a Solutions Lead with comprehensive understanding of the data lifecycle and the ability to architect tool-agnostic technical solutions. You will work across the full spectrum of data and AI capabilities, from analytics and engineering to data science and Generative AI, translating complex business problems into elegant, scalable technical solutions. As a trusted advisor to clients and a technical bridge within our team, you will shape solution designs that deliver real business value across major infrastructure programmes.

Core Responsibilities

• Lead end-to-end solution design for complex data and AI projects, from initial discovery through to implementation planning.
• Architect tool-agnostic technical solutions that span the entire data lifecycle, including ingestion, storage, processing, analytics, and AI applications.
• Conduct requirements gathering and stakeholder workshops, translating business challenges into well-defined technical solutions.
• Design integration architectures that connect disparate systems, data sources, and platforms.
• Evaluate and recommend appropriate technologies across the data and AI landscape, balancing client constraints with best practices.
• Create comprehensive solution documentation, including architecture diagrams, data flow designs, and technical specifications.
• Collaborate across disciplines, working with data engineers, analysts, and data scientists to ensure cohesive solution delivery.
• Support business development through solution design for proposals, estimates, and client presentations.
• Stay current with emerging technologies and industry trends, evaluating their applicability to client challenges.
• Provide technical guidance to delivery teams, ensuring solutions are implemented according to design principles.

 Technical Stack

Core:

·        Solution architecture across Azure ecosystem (Data Factory, Synapse, Databricks, Azure ML, Azure OpenAI),

·        Power BI,

·        SQL Server

Enhancements:

·        Tool-agnostic architecture patterns,

·        cloud platform comparison (Azure, AWS, GCP), API design,

·        microservices architecture,

·        data modelling

Desirable: 

·        Microsoft Fabric,

·        multi-cloud architectures,

·        enterprise integration patterns,

·        RAG architectures,

·        MLOps frameworks,

·        containerisation (Docker, Kubernetes)

 What You'll Bring: 

·        Professional experience spanning multiple areas of data and AI (analytics, engineering, or data science).

·        Strong understanding of the complete data lifecycle, from source systems through to business consumption.

·        Demonstrated ability to design technical solutions that are both pragmatic and innovative.

·        Experience with solution architecture, including creating architecture diagrams, data models, and technical specifications.

·        Broad technical knowledge across analytics platforms, data engineering tools, and AI/ML technologies.

·        Tool-agnostic mindset with ability to evaluate and recommend appropriate technologies for specific use cases.

·        Excellent communication skills, with ability to explain complex technical concepts to both technical and non-technical audiences.

·        Experience working in client-facing roles, with strong stakeholder management abilities.

·        Problem-solving orientation with a focus on delivering business value, not just technical elegance.

·        A strong commitment to Movar's IDEAL values: Integrity, Drive, Empathy, Adaptability, and Loyalty.

 Key Competencies

 Solution Design:

·        Ability to decompose complex business problems into technical requirements

·        Experience designing scalable, maintainable architectures across the data and AI stack

·        Understanding of trade-offs between different technical approaches

Cross-Disciplinary Knowledge:

·        Working knowledge of data analytics, data engineering, and data science practices

·        Understanding of Generative AI applications, including RAG architectures and LLM integration

·        Familiarity with cloud platforms, data governance, and security considerations

Communication & Collaboration:

·        Proven ability to facilitate workshops and gather requirements from diverse stakeholders

·        Experience creating clear, compelling technical documentation and presentations

·        Skill in bridging the gap between business needs and technical implementation

Technology Evaluation:

·        Ability to assess emerging technologies and evaluate their maturity and applicability

·        Experience conducting proof-of-concepts and technical feasibility studies

·        Understanding of licensing, cost, and operational considerations in technology selection