Data Engineer

Data Engineer at Wiz

Come join Wiz, the company reinventing cloud security and empowering businesses to thrive in the cloud. As the fastest-growing startup ever, Wiz is on a mission to help organizations secure cloud environments that will accelerate their businesses. Trusted by security teams all over the world, we have a proven track record of success and a culture that values world-class talent.

Our Wizards from over 20 countries work together to protect the infrastructure of our hundreds of customers, including over 50% of the Fortune 100, who trust us to scan and secure over 230 billion files daily. We’re the leading player in a massive and growing market, but it’s still early enough for you to make a significant impact. At Wiz, you’ll have the freedom to think creatively, dream big, and use your full range of skills to contribute to our record growth. Come join our team and help us create secure cloud environments that allow the best companies to move faster.

Summary

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'll Do

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

What You'll Bring

• Bachelor’s or Master’s degree in a relevant technical field, or equivalent hands-on experience in software development or DevOps.
• 3+ years of experience working as a Data Engineer, including end-to-end designing, orchestrating, and building cloud-based data pipelines (e.g., Airflow, Prefect, Dagster).
• 3+ years of experience with dimensional data modeling and data warehouse implementation, specifically MPP databases like BigQuery, Snowflake, and Redshift.
• Strong knowledge of Python and Python-based data analysis tools such as Jupyter Notebooks and pandas.
• Strong 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.
• Team player with excellent communication skills.
• Containerization (Docker): Essential for reproducible environments.
• Knowledge of software engineering best practices: CI/CD concepts, code reviews, and unit testing.

Advantage

• Production-level experience with 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.

Key skills/competency

• Data Engineering
• Cloud Data Pipelines
• Dimensional Data Modeling
• BigQuery
• Snowflake
• Python
• SQL
• dbt
• Docker
• CI/CD