Staff Data Engineer

2 дн. назад

SwitzerlandEuropeLeadOnsite

pythonsqlawskafkaspark

Staff Data Engineer role at focusing on AI-driven software development and code verification.

Who is Sonar? Sonar is driving the future of agent-centric software development. As the leader in AI code verification and governance, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable. Integrating seamlessly with Claude Code, Codex, Cursor, GitHub Copilot, Gemini, and Devin, we help over 75% of the Fortune 100 build trusted, reliable, compliant software. Customers who use Sonar are 44% less likely to report an outage due to AI-generated code. We believe code verification is the critical missing link in the Agent-Centric Development Cycle (AC/DC). Industry giants like Nvidia, ServiceNow,, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explaina

Design and implement data storage, transformation, and load capabilities of our pipelines.
Continuously enhance the data platform. Propose, implement and manage data handling services according to  stakeholders needs (Product Managers, Marketing, Sales, engineering teams, ...)
Establish top-class end-to-end pipelines including data cleaning and modelling.
Develop and deploy connectors to data sources of interest.
Maintain evergreen data flow documentation across systems.
Collaborate on Data Governance with other stakeholders/domains.
Work with the security function to ensure we adhere to expected security standards.
Collaborate with the incident manager to bring your expertise when asked and own implementation of recommendations from post-mortems.

You have solid software engineering experience, focusing on developing data engineering pipelines and storage in the cloud. You have been exposed to big data architecture essentials, streaming, ETL batches, data store administration, …
You see yourself as a developer working on data. You are motivated by both technical and functional aspects of services.
You are a friendly, enthusiastic, and organized team player. You actively share your knowledge and give and receive feedback to improve the team and yourself.
Strong experience building end-to-end ETLT, ETL, or ELT pipelines with batch or streaming technologies in Python.
Experience working with Databricks as a Platform or building data pipelines with PySpark is a plus.
Strong experience with the AWS platform including, but not limited to, services such as: Glue, RedShift, CloudFormation, S3, CloudWatch, Lambdas, etc… or equivalents
Good knowledge of data engineering concepts (Data Lake, Data Warehouse, etc…)
Experience with Infrastructure as code tools (CDK, CloudFormation, Terraform)
You are fluent in English, both written and spoken