Senior Solutions Architect (Databricks Specialist)
类别:IT 服务位置:我们正在寻找专业于数据的高级解决方案架构师,以提供战略领导和建筑监督,为领先金融服务组织内的大型数据现代化计划。客户端目前从传统的 SQL Server 和微软中心的数据生态系统转向一个基于 Databricks 的现代平台来支持其长期数据,分析和人工智能策略。虽然客户拥有既有能力的数据工程团队,但他们需要一位高级建筑师提供战略方向,实施框架,架构治理和最佳实践指导来确保成功且经济高效的转型。· 这一角色将集中在定义目标国家架构,制定标准和治理,优化平台设计,并确保技术投资与业务目标之间的协调。主要责任 · 为组织的 Databricks 实现和数据现代化倡议提供战略架构领导力。· 设计和定义与业务和人工智能目标一致的企业规模数据和分析架构。· 为采用 Databricks 制定并实施建筑框架,标准,模式和最佳实践。· 指导数据工程团队解决方案设计,可扩展性,性能优化,安全性和治理。·评估当前 SQL Server 和微软环境,并确定迁移战略到 Databricks. ·确保建筑决策支持未来 AI,机器学习,先进分析和报告要求。· 评估和优化平台利用以提高成本效率和最大限度地回报投资。· 建立治理,建筑审查流程和实施路线图。·提供高管层面的见解和建议关于技术方向,风险,机会和投资。·与业务利益相关者,技术领导,工程团队和供应商合作以实现成功结果。·监督解决方案质量并确保符合企业架构原则和法规要求。·确定技术风险,依赖性和潜在挑战,并在需要时实施减缓策略。· 辅导工程团队并促进项目中建筑卓越性。
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Category: IT Services
Location:
We are seeking an experienced Senior Solutions Architect specializing in Databricks to provide strategic leadership and architectural oversight for a large-scale data modernization program within a leading Financial Services organization.
The client is currently transitioning from a traditional SQL Server and Microsoft-centric data ecosystem to a modern Databricks-based platform to support its long-term data, analytics, and AI strategy. While the client has an established and capable Data Engineering team, they require a senior-level architect to provide strategic direction, implementation frameworks, architectural governance, and best-practice guidance to ensure a successful and cost-effective transformation.
- This role will focus on defining the target-state architecture, establishing standards and governance, optimizing platform design, and ensuring alignment between technology investments and business objectives.
Key Responsibilities
- Provide strategic architectural leadership for the organisation's Databricks implementation and data modernization initiatives.
- Design and define enterprise-scale data and analytics architectures aligned to business and AI objectives.
- Develop and implement architectural frameworks, standards, patterns, and best practices for Databricks adoption.
- Guide the Data Engineering team on solution design, scalability, performance optimization, security, and governance.
- Assess current SQL Server and Microsoft-based environments and define migration strategies to Databricks.
- Ensure architecture decisions support future AI, machine learning, advanced analytics, and reporting requirements.
- Evaluate and optimize platform utilization to drive cost efficiency and maximize return on investment.
- Establish governance, architecture review processes, and implementation roadmaps.
- Provide executive-level insights and recommendations on technology direction, risks, opportunities, and investments.
- Collaborate with business stakeholders, technology leadership, engineering teams, and vendors to drive successful outcomes.
- Oversee solution quality and ensure alignment with enterprise architecture principles and regulatory requirements.
- Identify technical risks, dependencies, and potential challenges, implementing mitigation strategies where required.
- Mentor engineering teams and promote architectural excellence across the program
Requirements
Required Technical Skills
Essential
- Deep expertise in Databricks architecture, implementation, and optimization
- Strong understanding of enterprise data platforms and modern data architectures
- Data Lakehouse architecture design and implementation
- Data governance, security, compliance, and data management frameworks
- Data migration strategy and execution
- Enterprise integration patterns and cloud-based architectures
- Analytics, Business Intelligence, and AI/ML platform enablement
Preferred
- Experience with Microsoft Azure Data Services
- Azure Data Factory
- Azure Synapse Analytics
- SQL Server
- Delta Lake
- Unity Catalog
- DataOps and DevOps practices
- AI and Machine Learning platform architecture
Essential Experience & Qualifications
- 10+ years of experience in Solution Architecture, Enterprise Architecture, or Data Architecture roles.
- Demonstrated experience delivering large-scale data transformation and modernization initiatives.
- Extensive experience designing and implementing Databricks solutions in enterprise environments.
- Proven track record supporting cloud migration and modern data platform programs.
- Experience within Financial Services, Banking, Insurance, or highly regulated environments.
- Strong understanding of data governance, security, compliance, and risk management frameworks.
- Experience developing enterprise architecture standards, frameworks, and governance models.
- Relevant certifications in Databricks, Cloud Platforms (Azure preferred), TOGAF, or related disciplines are highly advantageous.
Key Competencies
Strategic Leadership
- Ability to align technology architecture with long-term business strategy.
- Strong commercial acumen and focus on value delivery.
- Ability to influence technology direction at executive level.
Stakeholder Engagement
- Comfortable engaging with C-suite executives and senior business leaders.
- Strong communication, presentation, and facilitation skills.
- Ability to simplify complex technical concepts for non-technical audiences.
Architecture & Governance
- Excellent architectural design and decision-making capabilities.
- Strong focus on governance, standards, and best practices.
- Ability to drive consistency across multiple teams and initiatives.
Delivery & Outcomes
- Results-driven with a focus on business impact and measurable outcomes.
- Strong problem-solving and analytical thinking skills.
- Ability to work independently while guiding large technical teams.
Ideal Candidate Profile
The ideal candidate is a highly experienced Senior Solutions Architect with deep Databricks expertise, capable of providing strategic oversight to an established engineering team. They will bring extensive experience in enterprise data transformation, architecture governance, and cloud-based analytics platforms. The successful individual will be comfortable operating at executive level, influencing business and technology strategy, while ensuring Databricks is implemented in a scalable, cost-effective, and future-ready manner that supports the organisation's AI and data ambitions.
DetailsOriginally posted on Himalayas