Senior BI Data Engineer

Description

At Lusha, we’re building for builders. We build fast and AI-first - so we look for builders.

By a builder, we mean someone who turns “maybe” into “done”.

We’re looking for a Senior BI Data Engineer to join our BI team and take end-to-end ownership of high-impact analytics foundations. This role sits at the core of how Lusha measures success, makes decisions, and scales - turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.

You’ll design and evolve data models, pipelines, and the BI layer, work closely with Data Science and business stakeholders, and help raise the bar for analytics engineering across the company.

Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.

This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

This might be for you if:

• You enjoy owning data foundations end to end - from raw data to semantic layers
• You like turning ambiguous business questions into clear, governed metrics
• You care about data quality, performance, and trust at scale
• You enjoy mentoring, setting standards, and leading by example
• You actively leverage AI tools to improve development speed and analytical accuracy

Requirements

• 5+ years of experience in BI / Data Engineering roles with ownership of scalable data platforms
• Deep experience with modern data stacks (Snowflake or Databricks, dbt)
• Advanced SQL and Python skills, including data quality, CI/CD, and observability
• Strong understanding of dimensional modeling, data warehousing, and semantic layers
• Experience with orchestration tools (Airflow) and large-scale data processing
• Proven experience using GenAI tools as part of your day-to-day development workflow
• A strong builder mindset, business orientation, and ability to lead cross-functional initiatives

Nice to have:

• Experience with streaming technologies (Kafka, Spark)