Enterprise Architect
Job Description
Company: Bristlecone
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About the job
Job Summary The Enterprise Analytics Architect is responsible for designing and implementing scalable analytics solutions that align with the organization’s strategic goals
- This role bridges business needs with technical capabilities, ensuring data-driven decision-making across the enterprise
- The architect leads the development of analytics platforms, data integration strategies, and governance frameworks while mentoring teams and collaborating with stakeholders
Key Responsibilities Architecture & Strategy – Develop and maintain the enterprise analytics architecture, including data models, integration frameworks, and reporting platforms – Align analytics initiatives with business objectives and IT strategy – Design scalable, secure, and high-performance data solutions using modern technologies (e- g
- , cloud platforms, big data tools, machine learning frameworks)
Collaboration & Leadership – Work with business leaders, data scientists, and IT teams to identify analytics opportunities and requirements – Provide technical leadership and mentorship to analytics and data engineering teams – Serve as a subject matter expert in analytics platforms, data governance, and business intelligence Implementation & Optimization – Lead the design and implementation of ETL/ELT pipelines and data integration solutions – Ensure data quality, consistency, and compliance with regulatory standards – Optimize analytics systems for performance, scalability, and cost-efficiency Governance & Standards – Establish and enforce data architecture standards, policies, and best practices – Maintain documentation of architecture decisions, data flows, and system configurations – Evaluate emerging technologies and recommend adoption strategies
Qualifications Education – Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, Statistics, or related field Certifications (Preferred) – TOGAF, AWS/GCP/Azure Architect, CISSP, SAP BI, or similar
Experience – 12–15 years in enterprise data architecture, analytics, or business intelligence – Proven experience in designing and delivering mission-critical analytics solutions – Strong background in data modeling, cloud platforms, and big data technologies
Skills – Expertise in SQL, Python, R, and data visualization tools (e- g
- , Power BI, Tableau, SAP SAC)
– Familiarity with machine learning techniques and tools – Strong communication and presentation skills across technical and non-technical audiences – Ability to manage multiple projects in a fast-paced environment ~
