Jobs at Xebia

Lead product vision, roadmap and backlog for Salesforce-led customer service transformation. Define requirements, drive Service Cloud and omnichannel solutions, collaborate with stakeholders, support Agile delivery, UAT and change management, and apply AI-enabled automation to improve customer operations.

Design, build, and maintain Azure CI/CD pipelines and infrastructure; drive cloud migration and modernization; automate provisioning with Terraform; support .NET apps, Azure App Services/Functions, APIM and WAF; improve platform security, performance, and operational efficiency while collaborating with development and architecture teams.

Design, build, and maintain scalable data pipelines on GCP; optimize data models; ensure data quality; support legacy data migration; collaborate with teams; implement monitoring; contribute to data governance best practices.

Design and maintain GCP cloud platform solutions, manage Infrastructure as Code using Terraform, enhance CI/CD pipelines, and support migrations while ensuring reliability and performance.

The role involves developing and maintaining data ingestion pipelines, onboarding data sources, enhancing an Azure-based data platform, and improving data workflow management.

As a Ruby Developer, you will maintain and modernize Ruby on Rails applications, implement backend features, and ensure code quality through testing and CI/CD processes.

The Senior Java Developer will enhance client experiences using Agile practices, develop solutions in Java and related frameworks, collaborate with teams, mentor others, and manage project risks while driving best engineering practices.

The Data Platform Architect will oversee the design and implementation of a Snowflake-based data platform, ensuring architectural quality, managing technical dependencies, and collaborating with global teams while driving delivery and aligning with business objectives.

The Data Engineer will design, build, and maintain data pipelines, manage workflows using Apache Airflow, troubleshoot incidents, and collaborate on data delivery and validation processes.

Design, build, and maintain scalable batch ETL/ELT data pipelines and warehouse transformations (SQL-first). Model analytics-ready datasets, ensure data quality, lineage, governance and observability, and optimize processing jobs. Own dbt/semantic layers, collaborate with product/analytics/data science, enforce engineering standards, code reviews, and CI/CD practices to deliver reliable analytics and ML-ready data.

Design, build, and maintain scalable data pipelines using Palantir Foundry. Develop data workflows, models, and transformations (PySpark/SQL/Python), enable dashboarding and data virtualization, support AI/ML solutions, optimize performance and governance, collaborate cross-functionally, and contribute to architectural decisions within an Agile/Scrum environment.

Develop, optimize, and validate AI algorithms for advanced 3D cardiac medical imaging. Work on segmentation, reconstruction, mesh processing, deep learning model training and validation using clinical CT/MRI/echocardiography data. Collaborate with multidisciplinary teams, support regulatory evidence generation, improve algorithm robustness and performance, and mentor junior engineers.

Develop and maintain shared Python libraries and a schema management toolchain for a large distributed platform. Improve reliability, observability, CI/CD, and developer experience while collaborating with teams on reusable solutions and monitoring across event-driven systems.

Join a long-term digital transformation project as a QA Engineer, focusing on testing and quality assurance for a custom ERP system in logistics. Responsibilities include designing test cases, maintaining automation tests, collaborating with teams, and supporting various testing methodologies.

Design and build scalable ETL/analytics pipelines and curated datasets from multiple ERPs, create SQL-based reporting and BI dashboards, collaborate with stakeholders to define KPIs, and ensure multi-tenant, performant, documented data products that scale across customers.

Own and operate high-availability database clusters in Kubernetes: design StatefulSets/Operators/Helm charts, manage Helm-based GitOps deployments, perform zero-downtime upgrades and migrations, instrument and monitor performance/security, and develop Bash/Python automation to simplify Kubernetes database operations.

The role involves designing AI agents for operations, developing ML models, and integrating solutions into workflows while collaborating with teams.

Own product strategy and roadmap for scientific R&D platforms; drive discovery with researchers; translate bioinformatics requirements into product plans; manage backlogs in Jira/Confluence; collaborate with engineering, data platform, and architecture teams; define requirements and success metrics; support launch, adoption, modernization, and AI/GenAI adoption across scientific workflows on GCP.

Design and build analytics-ready data models and curated datasets (CRM-sourced) on cloud platforms. Collaborate with Data Engineering and Architecture to ensure data readiness, usability, quality, and consistency for reporting and business consumption.

Lead architecture for integrating CRM (Salesforce) into Azure/Databricks data platforms. Support presales with architect-level input, translate business and technical requirements into high-level designs, produce solution concepts, and identify risks, dependencies, and constraints while engaging stakeholders.