Lead Data Architect

Responsibilities

• Evaluate proposed project and data product scope, including delivery timeline, functional trade-offs, cost considerations, and expected business value.
• Translate business requirements into solution architectures aligned to the reference architecture, including infrastructure, data modeling, integration, and coding design considerations.
• Build alignment on proposed solution architectures and define phased implementation approaches that deliver early business value.
• Guide data engineering leads, data modelers, infrastructure specialists, and other team members on what must be designed, built, and tested to implement the solution successfully.
• Lead or support proofs of concept to validate new design patterns, technical approaches, or product features before broader implementation.
• Participate throughout the SDLC to help teams implement solution designs and meet business requirements and architecture objectives.
• Use feedback from delivery teams and stakeholders to improve future designs, frameworks, and practices that accelerate delivery and business value realization.
• Establish reusable detailed design patterns that can be adopted across multiple projects, including incubating new patterns through POCs or targeted design work.
• Deliverables / Results:
  • Project estimates with assumptions and estimating factors
  • Solution architecture diagrams
  • Decision trees on what technology or feature to use based on use cases
  • High level data model diagrams
  • High level data pipeline architecture diagrams
  • Alignment on coding standards and re-usable functions that should be built and shared by a project
  • Best practices and materials that project teams can use to align their build to the architecture, designs and re-usable frameworks
  • Impact / Value Add:
    • Business users achieve the business value as a result of the solution design and build
    • Solutions align to the architecture so other projects can leverage the solution built by a previous project
    • Integration of enterprise data so more insights can be produced

Qualifications

• Four year college degree or equivalent experience with Masters preferred
• Demonstrated on the job learning with certifications relevant to this position
• One or more hands skills from data modeling, coding, CI/CD implementation, and other components of a solution
• Using various software programs to produce the deliverables outlined above
• Architecture competency including architectural models, principles, levels of architecture, and business relevant application
• Strong knowledge of analytical and operational databases, data modeling, data pipeline design, coding frameworks, and programming languages used in modern data platforms
• General knowledge of cloud services, networking, security practices, and hardware configurations, and how they are integrated into a solution
• Experience designing ingestion solutions that use change data capture, event streaming, and batch processing for structured, semi-structured, and unstructured data sources
• Hands-on experience with Databricks, Spark, Kafka, ingestion tools, Lakehouse architectures, and related technologies that enable trusted, consumable business data