About the job AI Architect - Databricks focus
DATA & AI ARCHITECT
Data & Analytics Practice | Contract-to-Hire | Long-Term Oriented
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ENGAGEMENT DETAILS
- Type: Contract-to-hire, long-term oriented with direct hire potential
- Sponsorship: Not available — must be authorized to work in the US on a permanent basis
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WHY YOU'LL LOVE IT HERE
We invest in our people — at every level. Between projects you'll have access to funded education, certifications, and the latest tools in the data and AI space. Growth isn't just available, it's expected. You'll work alongside sharp colleagues on complex, meaningful problems — and have real influence over how solutions are designed and delivered.
We're a data-focused consultancy at the cutting edge of enterprise AI and modern data platforms. This isn't a seat-warming role. You'll shape strategy, lead client conversations, and build things that scale.
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THE ROLE
As our Data & AI Architect, you'll design, build, and scale enterprise data and AI solutions across the full lifecycle — from data ingestion and modeling through AI enablement, agent deployment, and production operations. You'll bridge the gap between business objectives and technical execution, guiding solutions from proof-of-value to enterprise scale across platforms like Databricks, Snowflake, and Microsoft Fabric.
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WHAT YOU'LL DO
Architecture, Strategy & Roadmapping
- Partner with business and technical stakeholders to translate enterprise challenges into data, analytics, and AI solution architectures — producing roadmaps, reference architectures, and implementation plans.
- Architect solutions that integrate with enterprise source systems, APIs, operational platforms, and downstream consuming layers.
- Establish design patterns and technical standards across data management, analytics, and AI — covering security, scalability, performance, lineage, and compliance.
Data Platform & Ecosystem Design
- Design and implement scalable data pipelines, transformation layers, and orchestration frameworks across platforms such as Databricks, Snowflake, Microsoft Fabric, GCP, or similar.
- Support dimensional modeling, feature stores, and semantic layers to enable BI, advanced analytics, and AI workloads.
- Design secure cloud architectures on AWS, Azure, or GCP — leveraging managed services, serverless patterns, and containerized workloads where appropriate.
AI Engineering & Agent Deployment
- Enable AI and ML workloads using curated, governed enterprise data — supporting model training, inference, and retrieval-based architectures (e.g., RAG).
- Design and deploy agentic and workflow-driven AI solutions incorporating orchestration, tool/function calling, guardrails, and observability for multi-step business processes.
- Lead Proof-of-Concept and pilot initiatives, validating business value and technical feasibility before scaling to production.
Delivery, Leadership & Enablement
- Review solution designs, contribute to critical implementation components, and mentor engineers across data engineering, analytics, and AI best practices.
- Partner with delivery leads and stakeholders to manage technical risks, trade-offs, and dependencies throughout project lifecycles.
- Support deployment, monitoring, and optimization of data and AI solutions to ensure reliability, performance, and long-term maintainability.
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WHAT YOU BRING
- 5+ years in data engineering, software engineering, or solution architecture — spanning data platforms and analytics or AI workloads.
- Strong hands-on experience with AWS or Azure, including data, analytics, and AI-related services.
- Proven experience designing or implementing solutions on Databricks, Snowflake, Microsoft Fabric, or similar platforms.
- Strong understanding of data ingestion, transformation, orchestration, and modeling patterns.
- Familiarity with Generative AI concepts (LLMs, embeddings, RAG), ML workflows, and how AI integrates with enterprise data platforms.
- Experience with AI agents, workflows, and business process automation best practices.
- Experience with CI/CD, model or pipeline deployment, monitoring, lineage, and governance tooling (e.g., MLflow, orchestration frameworks).
- Experience with microservices, APIs, event-driven architectures, and containerization.
- Proficiency in SQL, Python, Spark, and distributed data processing frameworks.
- Strong communication skills with the ability to explain architectural decisions to both technical and non-technical audiences.
- Consulting or customer-facing delivery experience.
- Ability to connect data and AI capabilities to measurable business outcomes.
- Must be authorized to work in the United States. Sponsorship is not available for this position.
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PREFERRED QUALIFICATIONS
- Degree in Computer Science, Data Engineering, Data Science, or a related field.
- Cloud or platform certifications (AWS, Azure, Databricks, Snowflake).
- Background in consulting or client-facing delivery environments.
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THE BIGGER PICTURE
AI is transforming how enterprises operate — but only when the data underneath it is solid. Our work lives at that critical intersection. If you want to build things that matter, work with a team that invests in your growth, and help clients unlock the real potential of their data, this is the role for you.