Senior Solution Architect

As Solution Architect for D&A, you'll bring energy, curiosity, and pragmatism to shaping Pandora’s D&A journey and direction and you will be responsible for designing and delivering end-to-end data platform solutions across our Data platform stack - Azure Synapse, and Databricks environments at Pandora.

 

In this hands-on architectural role, you will translate business requirements into technical solutions, work alongside lead engineers to propose architectural direction, and guide implementation across key transformation projects including SAP, Salesforce, POS and o9. Working "in the trenches" with engineering teams across supply chain, commerce, manufacturing, corporate tech and omni-channel, you will ensure solutions are scalable, maintainable, and aligned with data solution architecture principles, enabling Pandora's journey to becoming the world's leading jewellery company.

 

Key accountabilities include:

• Designing end-to-end data platform solutions (Azure Synapse platform, Databrick platform) that align with data solution architecture principles.
• Working directly with lead engineers to propose architectural direction, review technical designs, and ensure solutions meet scalability, performance, and maintainability requirements.
• Providing architectural guidance across transformation projects (SAP S/4HANA, Salesforce, o9, POS implementations) ensuring data integration patterns support business objectives.
• Designing integration architectures that connect source systems (SAP, Salesforce, o9, POS, e-commerce) to our data platform through our streaming platform Kafka.
• Architect Databricks wheels and DevOps artifacts and enablers for engineering teams.
• Architecting solutions for both centralised approaches (Synapse with CDM/RDM models, tabular models in Analysis Services) and lakehouse patterns (Databricks with decentralized principles).
• Reviewing and providing feedback on technical designs and code architecture from lead engineers, ensuring adherence to data platform standards and best practices.
• Defining and documenting solution patterns and best practices that builds quality across our data products.
• Leading technical design sessions with engineering teams, stakeholders, and lead engineers to solve complex data platform challenges collaboratively.
• Creating technical documentation including solution designs, architecture decision records (ADRs), data flow diagrams, and integration specifications.
• Supporting modernisation and migration from legacy to cloud-native solutions, designing transitional architectures that maintain business continuity.
• Mentoring teams on solution design patterns, cloud-native architecture, and data platform best practices through hands-on collaboration.

 

What is needed to succeed:

• 5-7+ years of hands-on experience designing and implementing data platform solutions with proven delivery of production-grade systems at scale.
• Strong Python development skills for data engineering workflows, and experience with orchestration frameworks and testing patterns.
• Strong SQL development skills including query optimization, indexing strategies, partitioning design, and performance tuning across SQL Server, Azure Synapse dedicated pools, and Databricks SQL.
• Deep experience with Databricks lakehouse architecture, working with Delta Lake features (ACID transactions, time travel, merge operations), implementing medallion architectures, and designing data products with clear interfaces.
• Technical expertise with Azure Synapse including designing star schemas and optimization techniques specific to each compute option.
• Practical experience designing end-to-end data pipelines including orchestration with Azure Data Factory or Databricks workflows, implementing error handling, retry logic, monitoring, and alerting patterns.
• Practical experience with streaming architecture and lambda architecture.
• Experience designing data quality frameworks as computational governance, embedding validation rules, data contracts, and quality checks within pipeline logic rather than post-processing validation.
• Demonstrated experience architecting solutions across both centralised patterns (dimensional modeling, Kimball, tabular models) and federated patterns (lakehouse, data mesh principles).
• Practical knowledge of tabular model design in Analysis Services, including DAX calculations, aggregations, partitioning strategies, and query performance optimization for Power BI consumption.
• Understanding of retail, manufacturing, finance or supply chain business processes and how data flows through a business.
• Strong collaboration skills working with lead engineers and development teams in a peer-based environment, pr