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About At-Bay
We are an insurance company built by cybersecurity experts, leveraging our technology and security expertise to better understand digital risks and, thus, build better insurance products and services. We help clients by providing insurance products, guidance on their security issues, and active risk management. Like software, digital risk is eating the world and we aim to empower businesses to thrive in this ever-changing landscape.
We are distributed globally with hubs in San Francisco, New York City, Atlanta, and Tel Aviv. We have aggressive plans to scale our business and believe the best way to make that happen is to immediately invest in further developing our teams.
What you'll do
Our BI team is the backbone of how At-Bay makes decisions. We own the data warehouse and the models behind underwriting, pricing, claims, finance, sales and product analytics - and increasingly, the data that powers AI agents and self-serve analytics across the company.
As a Senior BI Engineer, you will design and build the data models and pipelines that turn raw events from our platform and partners into trusted, well-documented data. You will partner closely with analysts, actuaries, product, and engineering, and help shape how we use modern tooling - including AI - to deliver data faster and more reliably.
Model the business: design and own dimensional and domain data models in Snowflake that serve as the single source of truth for key metrics.
Build reliable pipelines: develop incremental, tested and version-controlled transformations with dbt, Python and Airflow, ingesting data from internal services, SaaS tools and third-party APIs.
Own data quality: implement tests, data contracts, monitoring and alerting so stakeholders can trust the numbers.
Optimize performance and cost: tune queries, warehouses and models; keep Snowflake spend efficient as data volumes grow.
Enable self-serve and AI: build a well-defined semantic/metrics layer and clean, documented data that analysts, BI tools and LLM-based agents can query safely.
Work with AI-assisted tooling: use tools such as Claude Code / Copilot to accelerate development, and help the team adopt best practices around them.
Lead technical initiatives: drive POCs, migrations and architecture decisions, and raise the bar through code reviews and mentoring.
Partner cross-functionally: translate business questions from underwriting, finance, product and leadership into scalable data solutions.
Requirements
4+ years of experience as a BI Engineer, Analytics Engineer or Data Engineer
Expert SQL skills, including reading query plans and optimizing performance at scale
Strong experience in DWH design and dimensional modeling (Star schemas, SCDs, incremental loads)
Experience with Snowflake (performance tuning, cost management, RBAC)
Experience with orchestration tools such as Airflow, Dagster or similar
Hands-on experience with dbt in production (models, tests, macros, documentation)
Proficiency in Python for data pipelines, automation and integrations
Experience with Git-based workflows and CI/CD for data
Strong ownership - you take projects from ambiguous requirements to production
Excellent communication skills in English and Hebrew, and the ability to explain technical trade-offs to non-technical stakeholders
Nice to have
Experience with a semantic layer / metrics store and BI tools (e.g., Looker, Tableau, Power BI, Sigma)
Experience with data observability and quality tooling
Experience building data foundations for LLMs or AI agents (e.g., text-to-SQL, MCP, RAG over structured data)
Background in insurance, fintech or cybersecurity data
B.Sc. in Industrial Engineering & Management, Information Systems, Computer Science or a related field