Architect, Data & Analytics

Presidio

About The Position

The Data & Analytics Architect will be responsible for designing, developing, and implementing data & analytics solutions that empower data-driven decision-making for our clients. This role requires a strategic thinker with deep technical expertise in BI platforms, data modeling, and analytics, combined with strong consulting and client-facing skills. The ideal candidate must be self-directed and comfortable supporting multiple data solution implementations and client presales/sales scoping opportunities. The right candidate will be excited by the prospect of optimizing or even re-designing existing data platforms and solutions to support next generation of products and data initiatives, powered by AI. The candidate is expected to lead large data projects and teams across multiple client engagements.

Requirements

Bachelor’s degree or equivalent experience and/or military experience
7+ years in data solution build and architecture roles
10+ years of advanced working SQL knowledge and experience, with experience across multiple data modeling patterns

Nice To Haves

Experience with defining and executing on a data strategy a plus
Experience on Azure and GCP data stack is definitely a plus

Responsibilities

Define data solution architecture, including data integration, data warehousing, and reporting frameworks.
Develop scalable and secure data solutions aligned with client business objectives.
Design and optimize data models for analytics and reporting.
Oversee ETL processes and ensure data quality and governance.
Collaborate with clients to understand business requirements and translate them into technical solutions.
Provide thought leadership on BI best practices, emerging technologies, and industry trends.
Assist in Presales and client problem definition phase of an Azure data engagement. Work closely with the presales engineers to design the best-in-class Azure data solution and scoping to satisfy client requirements.
Ability to handle multiple client engagements in different stages of the implementation lifecycle.
Implement and manage BI tools (e.g., Power BI, Tableau, Qlik, Looker).
Ensure integration with enterprise systems and cloud platforms (Azure, AWS, GCP).
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
Monitor and enhance data system performance, scalability, and security.
Establish standards for dashboards, KPIs, and reporting.
Provide hands-on guidance, mentoring, and validation for the project teams during the implementation of the client engagement.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.