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Required Senior BI Analyst
About the role:
Data only creates value when people can see it, trust it, and act on it. As Senior BI Analyst, you own that last mile: the BI platform everyone opens to answer their questions, and the KPI definitions that make sure the numbers on every dashboard mean the same thing across every team.
This is the business-facing anchor of our analytics function. You'll build and govern the reporting layer, define the metrics that leadership runs the company on, and lead the Business Analyst guild - the network of domain analysts embedded across GTM, Finance, CS, and Product. You're equal parts platform owner, metrics authority, and enabler of the analysts around you.
If you love turning messy business questions into clear, trusted, self-serve answers - and raising the analytical bar for a whole company while you do it - this role is for you.
What youll own:
Own the BI platform end-to-end - Design and manage the dashboard architecture, set standards for report building and certification, manage access/governance, and keep the platform performant and trusted
Define and govern company-wide KPI metrics - Build a certified KPI catalog with documented logic and ownership; arbitrate metric definitions across teams so "win rate" means the same thing everywhere and is encoded once in the semantic layer
Drive self-serve analytics adoption - Empower stakeholders to answer their own questions by making the platform accessible, intuitive, and built on trusted definitions
Co-lead the Analytics guild - Convene and lead the company-wide community of practice connecting domain analysts; run enablement, tooling decisions, and reviews to keep everyone aligned on standards and the certified KPI catalog
Bridge analytics and engineering - Partner with the AI Data Engineer to ensure business definitions translate consistently into technical implementations across dashboards and AI agents
What you'll do day to day:
Design, build, and maintain governed dashboards and reports that stakeholders actually use.
Curate the certified KPI catalog - definitions, logic, ownership, and change control.
Partner with GTM, Finance, CS, and Product to translate business questions into clear, reusable metrics.
Drive self-serve BI adoption and reduce ad-hoc reporting requests.
Run the Business Analyst guild: standards, reviews, enablement, and tooling.
Work with data engineering to keep KPI definitions aligned with the semantic layer and underlying models.
Own the health of the BI platform: access, performance, certification, and cleanup.

Required AI Data Engineer
About the role:
We're building the intelligence layer that lets everyone ask hard questions of our data and get trustworthy answers - in plain language, in seconds. As AI Data Engineer, you own the semantic and AI-native surface of our Snowflake platform: the governed semantic layer that defines "what a metric means," the Cortex Agents that let business users query it conversationally, and the infrastructure that keeps all of it fast, reliable, and ready to scale.
This is a builder-owner role. You'll ship the semantic models, wire up the agents, and set the standard for how analysts across the company work with data. You'll also lead the Data Analyst guild - the connective tissue that keeps our hub-and-spoke analytics model coherent as it grows.
If you're excited by the space where data engineering, LLM tooling, and analytics governance meet, this role sits right in the middle of it.
What youll Own:
Snowflake semantic layer - Own the semantic layer end-to-end as the single source of truth for metrics; design semantic models, enforce naming standards, and ensure consistent metric definitions across dashboards and AI agents.
Cortex Agents - Design and deploy conversational AI agents using Cortex Analyst and Cortex Search; tune for accuracy and safety, expose through multiple surfaces (Snowflake Intelligence, Streamlit, MCP), and build evaluation harnesses to maintain quality at scale.
Data craft (Analytics guild) - Co-lead the technical track of the Analytics guild; set SQL and modeling standards, run technical enablement and code reviews, and serve as the technical authority for analysts.
Scaling data infrastructure - Improve performance, reliability, cost efficiency, and governance across the dbt/Airflow/Airbyte/Snowflake stack as data volume and query load grow; optimize warehouse sizing, medallion layers, and ingestion pipelines.
What you'll do day to day:
Model and maintain semantic views that power both dashboards and AI agents, keeping definitions versioned, tested, and certified.
Build, evaluate, and iterate on Cortex Agents - including retrieval quality, guardrails, and observability.
Extend and optimize dbt models, Airflow DAGs, and Airbyte connectors across bronze/silver/gold layers.
Partner with GTM, Finance, CS, and Product stakeholders to translate business questions into governed, reusable data assets.
Run the Data Analyst guild: standards, reviews, enablement, and tooling.
Own data quality, lineage, and cost monitoring across the Snowflake platform.
Expose data and agents through Streamlit apps, BI tools (Omni), and MCP servers for internal AI workflows.

CodeValue is looking for a DevOps Engineer to join a large-scale government project in Jerusalem. The role combines Cloud & DevOps infrastructure, CI/CD, monitoring and logging, automation, troubleshooting, and infrastructure security , while working closely with development, infrastructure, security, DBA, networking, and architecture teams.

Were looking for a Hands-on AI & Data Engineering Manager to lead a team building intelligent, large-scale consumer experiences powered by AI. In this role, you will lead engineers developing AI-driven products, work closely with data scientists, product managers, and designers, and ensure that AI capabilities-from LLMs and agents to product data insights-are translated into reliable, scalable production systems. You will be responsible not only for delivering AI features, but also for analyzing product data and user behavior to continuously improve AI performance and product outcomes. This is a technical leadership role combining engineering management, architecture ownership, AI product development, and data-driven decision making.
Key responsibilities:
Lead a team of data scientists, data engineers and product analysts
Own the delivery of AI-powered product capabilities, from research and experimentation to production and operation
Drive excellence, code quality, and best development practices
Provide technical direction and hands-on guidance for complex AI systems
Drive the integration of LLMs, AI agents, and intelligent workflows into core consumer experiences
Ensure AI solutions are safe, scalable, observable, and continuously improving
Lead initiatives around product data analysis and experimentation
Analyze user interactions with product features to improve accuracy, UX, and business impact
Partner with product teams to define metrics, dashboards, and experiments that guide product improvements
Design system architectures for AI-enabled applications at scale
Evaluate and select technologies for AI platforms and data pipelines
Guide the development of prompt engineering frameworks and centralized prompt management
Ensure robust monitoring, evaluation, and feedback loops for AI outputs
Translate product and business goals into technical roadmaps and execution plans
Drive alignment between AI capabilities and measurable product outcomes.

Required SRE / DevOps Lead
About the role:
As our SRE / DevOps Lead, you'll own the reliability, scalability, and security of the infrastructure that powers our platform - a system trusted by leading wealth managers, banks, and consumer fintechs to handle some of the most sensitive financial data their users have. You'll lead a team of 2 SREs and partner closely with product engineering, security, and our compliance partners to make sure what we build runs the way our customers (and the IRS) expect.
This is a hands-on lead role. You'll set the technical direction for our cloud platform, deployment pipelines, observability, and on-call practices - and you'll write the code, configs, and runbooks that get us there. You'll also own our IT function (identity, endpoints, SaaS) at a tighter scope, keeping the company secure and productive as we grow.
What you'll do:
Lead and grow a team of 2 SREs, setting direction across SRE, DevOps, and IT
Own the architecture, performance, and reliability of our GCP-based platform - Kubernetes, Terraform, CI/CD, networking, and scale
Define and uphold our SLOs, infra budgets, on-call priorities, and incident response practice
Build and operate our observability stack so engineers can find and fix problems before customers feel them
Partner with engineering and security on the controls, evidence, and audits that keep us SOC 2, SOC1 and STIG compliant and IRS-authorized
Plan and execute capacity, load testing, and game days for tax season - the highest-stakes window of our year
Own corporate IT: identity (Okta), Google Workspace, endpoint management (Jamf / Kandji), and the SaaS stack used across the company
Set the standard for how we ship: fast, safe, observable, and reversible.

we are establishing a strategic R&D center in Israel to drive the development of complex semiconductor chips that solve the critical 'data bottlenecks' enabling the future of AI at scale. As we expand our presence in Israel, we're seeking a talented Principal Emulation Engineer to help build our local engineering powerhouse from the ground up. This is an exciting opportunity to take on meaningful ownership in a new site, implementing the emulation strategy for chips that power the world's largest AI clusters.
As an Principal Emulation Engineer, you will be a core technical driver of our Israel R&D center, working at the intersection of hardware and software to ensure our silicon meets extreme quality and performance targets. You will execute end-to-end emulation flows, bridge the gap between RTL and functional validation, and partner with cross-functional teams to enable seamless hardware-software integration. If you thrive on solving complex technical challenges and want to play a key role in validating cutting-edge AI infrastructure connectivity solutions, this is your opportunity.
Key Responsibilities
Emulation Flow Execution & Implementation
Execute end-to-end emulation flow from high-level model generation and RTL synthesis to complex system-level testing and silicon-accurate debugging
Work directly with next-generation emulation platforms (Zebu, Palladium, or Veloce) to implement cutting-edge methodologies
Maintain and evolve emulation flows to reduce compile times and increase execution speed, directly impacting time-to-market
System-Level Debug & Validation
Drive initial model bring-up process in high-stakes environment, identifying and resolving complex bugs
Ensure rapid cycles from RTL to functional stability through systematic debug approaches
Own technical blocks and drive them to completion independently
Cross-Functional Collaboration
Partner with Firmware, Software, and Validation teams to debug complex system-level scenarios
Ensure seamless hardware-software integration for AI infrastructure connectivity
Collaborate with Design and Verification teams to optimize emulation strategies.