About this role
Designing dimensional models in Snowflake and building incremental data pipelines using dbt, Python, and Airflow form the core daily work for this position. The business intelligence team acts as the primary driver for organizational decision-making by managing the data warehouse and analytics models for underwriting, claims, finance, and product departments. Furthermore, this team increasingly prepares the data structures needed to power internal AI agents and self-serve reporting tools across the firm.
Joining At-Bay means taking charge of data quality through automated monitoring, optimizing query performance against growing datasets, and collaborating directly with actuaries, analysts, and software engineers. Ideal candidates bring strong engineering foundations, possess an ownership-driven mindset, and can effectively translate complex business requirements from leadership into reliable, production-ready data solutions.
What you will do
- Design and maintain dimensional data models within Snowflake to establish a single source of truth for key business metrics.
- Develop version-controlled data pipelines utilizing dbt, Python, and Airflow to ingest information from internal services and third-party tools.
- Implement robust data quality checks, automated tests, and monitoring protocols to maintain stakeholder trust in reported metrics.
- Optimize query performance and warehouse compute costs to ensure efficient scaling as platform data volumes expand.
- Build semantic layers and clean datasets that enable analysts, BI tools, and LLM-based agents to query information safely.
- Leverage AI-assisted coding tools to accelerate development workflows while establishing team best practices.
- Drive technical migrations, proofs of concept, and architecture decisions through code reviews and mentorship.
- Collaborate across departments with underwriting, finance, and product teams to deliver scalable data solutions.
What you need
- Bring four or more years of professional experience working as a BI Engineer, Analytics Engineer, or Data Engineer.
- Demonstrate expert-level SQL capabilities, including the ability to analyze query execution plans and optimize scale performance.
- Possess hands-on production experience with data warehouse design, dimensional modeling, and star schemas.
- Show documented background managing Snowflake environments, covering cost controls, RBAC, and performance tuning.
- Operate comfortably with orchestration platforms such as Airflow or Dagster alongside production dbt deployments.
- Write proficient Python code to build data pipelines, manage automation tasks, and handle third-party integrations.
- Maintain fluency in Git-based workflows and CI/CD pipelines tailored for data engineering.
- Communicate fluently in both English and Hebrew while possessing the skill to explain technical trade-offs to non-technical partners.
Nice to have
- Experience with a semantic layer, metrics store, or business intelligence tools such as Looker, Tableau, Power BI, or Sigma.
- Familiarity with data observability and quality platforms.
- Background building data foundations to support LLMs or AI agents, including text-to-SQL or RAG implementations over structured data.
- Previous domain experience within insurance, fintech, or cybersecurity sectors.
- Bachelor of Science degree in Industrial Engineering and Management, Information Systems, Computer Science, or a related field.
Benefits
- Competitive salary and benefits package
- Work-life balance with a hybrid schedule requiring three days in the office
- Office location in Tel Aviv near the train station and main bus stops
Skills and tech stack
Questions candidates ask
What is the remote work and office policy?
The role follows a hybrid work schedule requiring three days in the office. The office is located in Tel Aviv near the train station and main bus stops.
What technologies and tools will I use?
The core stack includes Snowflake, dbt, Python, Airflow, PostgreSQL, MySQL, AWS, and Git or GitHub Actions. The team also uses AI-assisted development tools such as Claude Code and Copilot.
Who will I work with across the company?
You will partner closely with analysts, actuaries, product teams, and engineering. The position also involves translating business questions from underwriting, finance, product, and leadership into data solutions.