Similarweb

Senior BI Engineer

Tel Aviv, Israel

Actively hiring, first seen by us 9 days ago

Pay: Pay not listed
Work setting: Hybrid — work setting source
Senior BI Engineer Location: Givatayim, Israel Experience: 5+ Years Work model: Hybrid We Are
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Employment: Not stated

What you’ll work on

Full posting

Turn raw data into clean, well-structured tables that analysts can query easily
Translate product and marketing metric concepts into precise SQL definitions
Keep metrics consistent and reliable across product and business reports
Design and maintain modular, tested dbt data models
Ship analytics code through pull requests, automated tests and deployments

From the employer’s posting

Take raw, complex data and transform it into clean, well-structured tables

Work with Product, Marketing, GTM analysts to turn abstract concepts into precise SQL definitions

ensure that the numbers used across our product and business reports are consistent, reliable, and logical

Design, build, and maintain production-grade data models using dbt

Work through pull requests, automated tests and deployments (GitHub/GitLab)

Apply at Similarweb

Posting record

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Actively hiringFirst seen by us 9 days ago, still listed, and not a repost of an earlier posting.

Status in our records: Live
First seen by us: Oct 26, 20269 days ago
Recorded sightings: 11
Last seen by us: Nov 4, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 9

Similar jobs usually come down between day 6 and day 47.

From 1,409 similar postings that came down. Coming down is not always a hire.

Similarweb is hiring

15 open jobs

Open jobs by the week we first saw them, last 12 weeks.

Hiring at a steady pace
Takes jobs down at a usual pace

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

Python
SQL
Databricks
dbt
Prefect
Redshift
Snowflake
Airflow
Dagster

Where the posting names them

We Are Looking For We are looking for an experienced talented BI Engineer to join our Data team in Givatayim. You will take end-to-end ownership of our data modeling, serving as the architect of the "Source of Truth" that powers our company's most critical strategic decisions. This is a hands-on engineering role: you will ship production code (SQL, dbt, Python) through a Git-based CI/CD workflow, use AI coding tools to move faster, build and implement AI based solutionsto turn the data into a critical part of decision making. What You’ll Do

CI/CD & Git Workflows: Hands-on experience with Git and CI processes for data projects: pull-request reviews, automated tests on every change, and automated deployments of dbt projects.AI-Assisted Development: Practical, day-to-day experience using AI coding tools (Cursor, Claude Code) to build faster, and the judgment to review and validate AI-generated code before it ships. - Python : Experience with Python for data orchestration or custom transformationsAdvantages: Orchestration: Experience with an orchestration tool (such as Airflow / Dagster / Prefect) for scheduling and monitoring data workflows.Data Quality & Observability: Experience with automated data tests, data contracts, monitoring, and alerting that keep stakeholders’ trust in the numbers.Data for AI: Experience building data foundations for LLMs or AI agents, such as semantic/metrics layers, text-to-SQL, or MCP-based data access.Performance & Cost: Experience tuning queries, models, and warehouse usage to keep the analytical data warehouse fast and cost-efficient.

- Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making. You know how to build a table that is intuitive and easy for other analysts to query. - Translate Strategy into Logic: Work with Product, Marketing, GTM analysts to turn abstract concepts into precise SQL definitions and automated datasets. - Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.

- Experience of 5+ years of prior experience in a relevant analytics/technical role (Analytics Engineer, BI Engineer, BI Developer or Data Engineer). - SQL Mastery: Expert-level SQL skills. You can write complex queries, optimize performance, and debug legacy code with ease. - dbt Expertise: Proven hands-on experience with dbt. You are comfortable with Jinja templating, incremental models, and package management.

- Python : Experience with Python for data orchestration or custom transformationsAdvantages: Orchestration: Experience with an orchestration tool (such as Airflow / Dagster / Prefect) for scheduling and monitoring data workflows.Data Quality & Observability: Experience with automated data tests, data contracts, monitoring, and alerting that keep stakeholders’ trust in the numbers.Data for AI: Experience building data foundations for LLMs or AI agents, such as semantic/metrics layers, text-to-SQL, or MCP-based data access.Performance & Cost: Experience tuning queries, models, and warehouse usage to keep the analytical data warehouse fast and cost-efficient. Our Stack:

Our Stack: Redshift, dbt, Databricks ,Airflow, GitLab,Cursor - any experience with similar tools is relevant. Why Join Us?

- Enable High-Tech Initiatives: Partner with our AI and Data Service specialists to ensure they have the structured data foundations they need to build models and external data products. - Build Scalable Models: Design, build, and maintain production-grade data models using dbt, ensuring code is modular, tested, and documented. Engineer with CI/CD Discipline: Treat analytics code like software. Work through pull requests, automated tests and deployments (GitHub/GitLab), code reviews, and version-controlled environments, so every change to the Source of Truth is tested before it ships.Build with AI: Use AI coding assistants (Cursor, Claude Code) in your daily workflow to speed up modeling, testing, documentation, and code review, and help the team define how we use them responsibly.Make Data AI-Ready: Build well-documented models with clear definitions and a consistent metrics layer, so analysts, AI agents, and data products can rely on the same trusted data.

- SQL Mastery: Expert-level SQL skills. You can write complex queries, optimize performance, and debug legacy code with ease. - dbt Expertise: Proven hands-on experience with dbt. You are comfortable with Jinja templating, incremental models, and package management. - Data Modeling: Experience with ETL processes and strong understanding of data warehousing concepts (Amazon Redshift/ Snowflake) and modeling methodologies .

- Product & Business Acumen: You understand SaaS metrics (ARR, funnels, activation, etc.) and how data logic impacts product growth and strategy. CI/CD & Git Workflows: Hands-on experience with Git and CI processes for data projects: pull-request reviews, automated tests on every change, and automated deployments of dbt projects.AI-Assisted Development: Practical, day-to-day experience using AI coding tools (Cursor, Claude Code) to build faster, and the judgment to review and validate AI-generated code before it ships. - Python : Experience with Python for data orchestration or custom transformationsAdvantages:

- dbt Expertise: Proven hands-on experience with dbt. You are comfortable with Jinja templating, incremental models, and package management. - Data Modeling: Experience with ETL processes and strong understanding of data warehousing concepts (Amazon Redshift/ Snowflake) and modeling methodologies . - Product & Business Acumen: You understand SaaS metrics (ARR, funnels, activation, etc.) and how data logic impacts product growth and strategy.

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About the role

We file this job under Analytics Engineer, by the work the posting describes.

Analytics engineers turn raw warehouse data into clean, tested and documented tables that analysts and dashboards can rely on, often with dbt.

Expect strong SQL, data modeling, Git, and a warehouse such as Snowflake, BigQuery or Redshift.

A data engineer gets data into the warehouse; an analytics engineer shapes it once it is there and works closer to the analysts who use it.

US government figures for database architects

Median yearly pay, May 2025: $139,500
Expected change, 2025 to 2035: 9.4% more jobsagainst 3.5% for all jobs

The government has no code for analytics engineers, so these figures are for the closest group, database architects, the same group we use for data engineers.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.

Job description

View original posting ↗

Senior BI Engineer

Location: Givatayim, Israel Experience: 5+ Years Work model: Hybrid

We Are

At Similarweb, we’re revolutionizing how businesses understand the digital world by showing them everything that happens online. Our unique data and solutions empower over 13,000 customers worldwide -including Google, eBay, and Adidas - to make game-changing decisions that drive their digital strategies. We went public on the New York Stock Exchange in 2021, and we’re still reaching new heights! Come join Similarwebbers across the globe who are bright, curious, practical, and genuinely good people.

We Are Looking For

We are looking for an experienced talented BI Engineer to join our Data team in Givatayim. You will take end-to-end ownership of our data modeling, serving as the architect of the "Source of Truth" that powers our company's most critical strategic decisions. This is a hands-on engineering role: you will ship production code (SQL, dbt, Python) through a Git-based CI/CD workflow, use AI coding tools to move faster, build and implement AI based solutionsto turn the data into a critical part of decision making.

What You’ll Do

Define the Source of Truth: Take raw, complex data and transform it into clean, well-structured tables that Product Analysts and Business Leads can use for high-stakes decision-making. You know how to build a table that is intuitive and easy for other analysts to query.
Translate Strategy into Logic: Work with Product, Marketing, GTM analysts to turn abstract concepts into precise SQL definitions and automated datasets.
Maintain Data Integrity: Act as the guardian of our metrics. You will ensure that the numbers used across our product and business reports are consistent, reliable, and logical.
Enable High-Tech Initiatives: Partner with our AI and Data Service specialists to ensure they have the structured data foundations they need to build models and external data products.
Build Scalable Models: Design, build, and maintain production-grade data models using dbt, ensuring code is modular, tested, and documented.

Engineer with CI/CD Discipline: Treat analytics code like software. Work through pull requests, automated tests and deployments (GitHub/GitLab), code reviews, and version-controlled environments, so every change to the Source of Truth is tested before it ships.Build with AI: Use AI coding assistants (Cursor, Claude Code) in your daily workflow to speed up modeling, testing, documentation, and code review, and help the team define how we use them responsibly.Make Data AI-Ready: Build well-documented models with clear definitions and a consistent metrics layer, so analysts, AI agents, and data products can rely on the same trusted data.

Take part in building Agentic solutions to support 24X7 solutions

This is a perfect job for someone who has:

Experience of 5+ years of prior experience in a relevant analytics/technical role (Analytics Engineer, BI Engineer, BI Developer or Data Engineer).
SQL Mastery: Expert-level SQL skills. You can write complex queries, optimize performance, and debug legacy code with ease.
dbt Expertise: Proven hands-on experience with dbt. You are comfortable with Jinja templating, incremental models, and package management.
Data Modeling: Experience with ETL processes and strong understanding of data warehousing concepts (Amazon Redshift/ Snowflake) and modeling methodologies .
Product & Business Acumen: You understand SaaS metrics (ARR, funnels, activation, etc.) and how data logic impacts product growth and strategy.

CI/CD & Git Workflows: Hands-on experience with Git and CI processes for data projects: pull-request reviews, automated tests on every change, and automated deployments of dbt projects.AI-Assisted Development: Practical, day-to-day experience using AI coding tools (Cursor, Claude Code) to build faster, and the judgment to review and validate AI-generated code before it ships.

Python : Experience with Python for data orchestration or custom transformationsAdvantages:

Orchestration: Experience with an orchestration tool (such as Airflow / Dagster / Prefect) for scheduling and monitoring data workflows.Data Quality & Observability: Experience with automated data tests, data contracts, monitoring, and alerting that keep stakeholders’ trust in the numbers.Data for AI: Experience building data foundations for LLMs or AI agents, such as semantic/metrics layers, text-to-SQL, or MCP-based data access.Performance & Cost: Experience tuning queries, models, and warehouse usage to keep the analytical data warehouse fast and cost-efficient.

Our Stack:

Redshift, dbt, Databricks ,Airflow, GitLab,Cursor - any experience with similar tools is relevant.

Why Join Us?

Impact: You are the architect of the data that drives our engines. Your work literally powers the team's ability to innovate.
Growth: You will work on the cutting edge of the data stack, gaining exposure to AI implementation and high-scale data logic.
Collaboration: Our best work comes from face-to-face teamwork in the office, with flexibility to work part-time from home.
Culture: We’re inclusive, innovative, and supportive. We foster open dialogue and encourage big ideas.
Perks: Competitive compensation, strong emphasis on well-being, comprehensive equity packages, and plenty of opportunities for team bonding.

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