Enterprise Context Architect

Opportunity Overview We're hiring a Data Architect who will serve as a senior technical leader responsible for architecting the complete lifecycle data moves, transforms, and creates value across every product line we operate. You'll own the blueprint for our enterprise data lakehouse - setting the standards, governance, and strategy that elevate data from a byproduct of operations to the company's most valuable asset. We need someone who pairs deep mathematical and logical modeling expertise with a builder's instinct - someone who codes, prototypes fast, and proves out next-generation AI data architectures before committing the organization to them. This role would need experience with US healthcare domain data. What You'll Do Semantic Layer Governance: Set the technical standard and reference architecture for a universal semantic layer across multiple distinct data products, ensuring unified definitions of complex metrics and healthcare business entities across Architect the Enterprise Context Layer: Define, scale, and govern the global Enterprise Ontology (abstract domain maps, business entity classes, and entity-relationship rules) that serves as the backbone for Agentic AI systems. AI-Native Prototyping : Leverage modern AI-native development environments (such as Cursor, GitHub Copilot) to rapidly generate, iterate, and document blueprints for complex enterprise data schemas and metadata layers. Security & Compliance Leadership : Embed regulatory compliance (HIPAA, FHIR) and security principles into platform design. Partner with security and compliance teams to ensure architectural decisions support audit readiness and risk mitigation. Cross-Functional Collaboration : Partner with executive leadership, product management, and engineering to translate business requirements into scalable technical solutions. Communicate complex architectural concepts to both technical and non-technical stakeholders. ISMS roles and responsibilities Good knowledge of Informati

The Engineering Lead Analyst – SonarQube & Code Quality Engineering is a senior-level engineering role responsible for leading static code analysis, automated code quality governance, security vulnerability remediation, and AI-augmented developer enablement across enterprise software delivery pipelines. In this role, you will champion software reliability, maintainability, clean-coding standards, and automated quality gates. You will partner with development teams, system architects, and platform engineering to integrate and manage enterprise-scale code quality platforms (such as SonarQube) both on-premises and in cloud/SaaS environments. Additionally, you will drive modern engineering practices by embedding Behavior-Driven Development (BDD) within your own software delivery and leveraging Agentic AI workers and Model Context Protocol (MCP) architectures to optimize developer experience, streamline code governance, and boost engineering velocity. Key Responsibilities 1. Code Quality & Static Analysis Platform Ownership Lead the architecture, deployment, administration, and continuous enhancement of enterprise Static Application Security Testing (SAST) and Code Quality platforms (e.g., SonarQube , DeepSource, Codacy, Semgrep). Configure, calibrate, and enforce automated Quality Gates, code rulesets, technical debt calculation models, and code-coverage baselines across multi-language enterprise repositories. Oversee version upgrades, patching, high availability, and operational maintenance for on-premises and SaaS/cloud-hosted code quality infrastructure. 2. CI/CD & Pipeline Integration <li style=

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Data Engineering - Applied Field Engineer- CA- Menlo Park- Remote Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. Our Solution Engineering organization is seeking a Data Engineering Specialist to join our Applied Field Engineering team who can provide technical leadership in working with both technical and business executives in the design and architecture of the Snowflake Cloud Data Platform as a critical component of their enterprise data architecture and overall ecosystem. In this role you will work directly with the sales team to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. You will leverage your expertise, best practices and reference architectures highlighting Snowflake’s Data Platform capabilities across data ingestion, transformation, and lakehouse workloads. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with tec

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake is about empowering enterprises to achieve their full potential — and people too. With a culture that’s all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology — and careers — to the next level. Our Solution Engineering organization is seeking a Senior Data Platform Architect (Specialist) to join our Applied Field Engineering team who can provide technical leadership in working with both technical and business executives in the design and architecture of the Snowflake Cloud Data Platform as a critical component of their enterprise data architecture and overall ecosystem. In this role you will work directly with the sales team to understand the needs of our customers, strategize on how to navigate winning sales cycles, provide compelling value-based demonstrations, support enterprise Proof of Concepts, and ultimately close business. You will leverage your expertise, best practices and reference architectures highlighting Snowflake’s Data Platform capabilities across data ingestion, transformation, and lakehouse workloads. You are equally comfortable in both a business and technical context, interacting with executives and talking shop with technical audiences. IN THIS ROLE YOU WILL GET TO: Ap

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The divide between business needs and technical delivery is one of the most persistent challenges in enterprise technology, where People teams struggle to articulate requirements and engineering teams lack the business context to build truly impactful solutions. As a Senior Business Solution Architect for People at Lyft, you'll eliminate this gap by serving as the critical connection point between our People teams and our Corporate Engineering and IT (CEIT) organization. This customer obsessed role uniquely combines deep functional business expertise with strong technical acumen, with an AI native approach, enabling you to translate complex business needs into systemized, scalable solutions while driving AI-enabled transformation across the People function. We're seeking a strategic thinker who thrives at the intersection of business and technology, possesses exceptional communication skills across both technical and non-technical audiences, and is dedicated to architecting the future AI Native state of how the People function operates. You'll be the trusted advisor to both business leaders and engineering teams, ensuring our People organization has systems and processes that scale with our business while our engineering teams build solutions that truly move the needle. With AI fundamentally reshaping how the People function gets work done, your expertise will be critical in helping us responsibly harness these technologies to drive operational excellence. In this role, you'll reimagine People workflows through an AI-first lens, design business processes that balance operational excellence with technical feasibility, and champion automation that elevates teams from tactical execution to strategic impact. If you are a candidate who has the vision of what could be, who has the ability to cultivat

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an