Staff Data Engineer

Sonarsource·Genevamid

En corto

→Ingeniero de datos que construye plataformas de datos para decisiones basadas en datos.
→Diseña y mantiene pipelines ETL/ELT con Python, Spark y AWS, trabajando con equipos de producto y seguridad.
→Trabajas en un entorno de alta velocidad con impacto directo en la calidad del código generado por IA.

Proficiency in English is required for collaboration across global teams.

En ~1 minuto te damos: quién te entrevista, las preguntas probables con respuestas desde tu CV, y tu CV adaptado a esta vacante. Gratis, sin tarjeta.

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¿Qué piden?

✓Experiencia sólida en desarrollo de pipelines ETL/ELT con Python.
✓Conocimiento avanzado de arquitecturas de big data y procesamiento de datos en la nube.
✓Experiencia con AWS (Glue, RedShift, S3, CloudWatch, Lambdas, CloudFormation).
✓Experiencia con Databricks y PySpark es un plus.
✓Capacidad para colaborar con múltiples equipos (producto, marketing, seguridad).
✓Enfoque de desarrollador con atención al detalle y a la calidad del código.

¿No cumplís todo? Es lo normal — tu dossier gratis te dice qué gaps tenés y cómo cubrirlos en la entrevista.

PythonPySparkDatabricksAWSGlueRedShiftS3CloudWatchLambdaCloudFormation

¿A quién escribirle en Sonarsource?

Tu dossier gratis identifica a las personas que te entrevistarían — con su background, qué valoran y cómo escribirles para destacar antes de aplicar.

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). com, Goldman Sachs, AstraZeneca, and Ford Motor Company count on us to provide independent, explainable, consistent review and governance of their AI-generated code via products like: SonarQube: The world’s leading AI code review and verification platform. SonarQube Foundation Agent: Currently topping the leaderboards for agentic software repair. SonarSweep & Sonar Context Augmentation: Providing the enterprise-grade context and constraints agents need to be truly effective. C. We move with a mindset we call CODE: Committed to our customers and community. Obsessed with quality. Deliberate in our decisions. Effective as one team. With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution. If you’re hungry to have an impact, want to build at a fast pace, and ready to work at the forefront of AI, we want to hear from you. Position description: We want to make the best decisions possible for our products and to do that, we need to make data-driven decisions. To achieve this goal, we are looking for a talented Data Engineer - you! - to join the Data & ML Platform team. Together, we will make Sonar’s products the undisputed world-leading code remediation solution! What you will do You will design and develop the data platform to support the functional domains in handling their data and help them in their journey to data ownership. This means: 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. Experience and qualifications 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.

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