Data Engineer

Wiz Wiz · Enterprise · Tel Aviv, Israel · BI & Data

We’re looking for a talented Data Engineer to join our Data team and spread the power of Wiz. The Data team develops and maintains the infrastructure for internal data and product analytics. We are looking for data enthusiasts, independent, logical thinkers with a can-do approach and a passion for problem-solving. We run a SaaS-based stack using BigQuery, Snowflake and dbt.

What you'd actually do

  1. Design, build, and maintain data pipelines, datasets and catalogs for fast-growing products and business groups.
  2. Develop self-service data analytics solutions and infrastructure.
  3. Support ad hoc needs and requests of internal stakeholders.
  4. Collaborate with analysts, engineers, and internal customers from Product, Finance, Revenue, and Marketing.

Skills

Required

  • 3+ years of experience working as a Data Engineer
  • end-to-end designing, orchestrating, and building cloud-based data pipelines (e.g., Airflow, Prefect, Dagster)
  • dimensional data modeling and data warehouse implementation, specifically MPP databases like BigQuery, Snowflake, and Redshift
  • Python and Python-based data analysis tools such as Jupyter Notebooks and pandas
  • SQL writing skills
  • Ability to write highly performant queries
  • Strong track record of executing projects independently in dynamic environments
  • Fast understanding of data and business needs and ability to translate them into data models
  • Containerization (Docker): Essential for reproducible environments
  • Knowledge of software engineering best practices: CI/CD concepts, code reviews, and unit testing

Nice to have

  • dbt, including project design, transformation, testing, and documentation
  • Infrastructure-as-Code (Terraform): Managing cloud resources (S3 buckets, IAM roles) via code
  • CI/CD pipelines (GitHub Actions/Jenkins): Automating the testing and deployment of data models

What the JD emphasized

  • end-to-end designing, orchestrating, and building cloud-based data pipelines
  • dimensional data modeling and data warehouse implementation
  • Strong track record of executing projects independently in dynamic environments