Jobs at Xebia

Gather, analyze, and document business and functional requirements for Data Quality monitoring and migration initiatives. Define metrics, validation rules, business logic, and acceptance criteria; facilitate stakeholder workshops; translate business needs into technical specifications; identify gaps and dependencies; support UAT and business testing; validate migrated controls; compare solution results; and maintain functional documentation.

Designs, develops, and maintains automated frontend and backend tests using C#, Selenium, Playwright, and RestSharp. Performs manual, API, accessibility, web, and desktop application testing; integrates tests into CI/CD pipelines; supports quality throughout the SDLC; and collaborates with development teams to resolve defects. The role also uses AI-powered assistants and explores GenAI practices in software delivery.

Build and maintain Event Hub and Databricks data pipelines, silver and gold data layers, data products, models, dashboards, and serving architecture. Analyze media usage data, support analysts, translate business requirements into technical specifications, and collaborate with data engineering teams. Contribute to CI/CD and software development practices using GitHub, GitHub Actions, and AI-assisted tools.

Build and maintain data pipelines and ELT processes, implement data quality metrics and controls using dbt and BigQuery, migrate legacy data quality solutions, integrate with GCP services, optimize execution performance, support testing, and document technical and operational processes. Collaborate with data modelers, business analysts, and test engineers on data transformation and monitoring solutions.

Build and maintain Databricks workspaces, platform services, infrastructure-as-code, deployment frameworks, and CI/CD pipelines. Automate provisioning and release management, support Unity Catalog governance, data ingestion, disaster recovery, resiliency testing, validation, change control, and operational support. Collaborate with cloud, SRE, architecture, and engineering teams in enterprise and regulated environments, including platform handover and knowledge transfer.

Designs and optimizes Google Cloud data platforms, ETL/ELT pipelines, Spark workloads, Airflow DAGs, and event-driven orchestration. Manages Bronze, Silver, and Gold data layers in Google Cloud Storage, implements reprocessing and backfill capabilities, improves metadata-driven tooling, and optimizes performance, cost, observability, and reliability. Collaborates with platform, analytics, and DevOps teams to support production data pipelines.

Define and document data governance operating models, metadata processes, ownership frameworks, classification standards, lineage practices, and business processes. Gather requirements, connect business knowledge to technical assets, support governance implementation in Knowledge Catalog, and prepare project documentation. Facilitate stakeholder workshops, training, knowledge transfer, and change adoption while collaborating with cross-functional business and technical teams.

Designs, develops, and maintains dbt-based transformation frameworks and analytical data models across Silver and Gold layers. Optimizes dbt execution, BigQuery-based transformations, cloud processing costs, and operational workflows. Manages dbt artifact versioning, Docker-based deployment, data quality, governance, and technical documentation while collaborating with Data Engineering, DevOps, and Platform teams.

Designs and maintains CI/CD pipelines, reusable delivery templates, deployment automation, artifact distribution, Docker workflows, and Kubernetes environments. Automates platform engineering activities, supports Python packaging migrations from Poetry or setuptools to UV, and improves software delivery governance, traceability, and repeatability. The role also collaborates with engineering teams on DevOps practices and maintains technical documentation, with opportunities to support GCP-based enterprise data platforms.

Design, configure, and enhance Google Knowledge Catalog solutions; build metadata integrations, enrichment, lineage, governance, access management, monitoring, and deployment automation. Conduct technical analyses and proofs of concept, document solutions, and support operational handover, readiness, and knowledge transfer while collaborating with governance and platform stakeholders.

Develop full-stack applications using Java, Spring Boot, Angular, REST APIs, PostgreSQL, and Domain-Driven Design. Integrate LLMs and Generative AI APIs to transform unstructured data into structured content and build AI-powered enterprise features. Collaborate in fast-paced PoC and MVP environments, adapt solutions to customer feedback, and use AI development assistants to improve delivery quality and productivity.

Design and implement scalable Databricks data pipelines, standardize and migrate legacy pipelines, develop dbt and Python transformations, onboard regional datasets, optimize performance and resource usage, and collaborate with architects and analytics teams. The role also contributes to future Data Science and MLOps foundations while supporting cloud-based data platforms and data modeling practices.

Develop production-grade TypeScript applications, backend services, APIs, system integrations, and agentic AI orchestration workflows. Integrate AI agents with external tools and existing systems, build cloud-based solutions using AWS, and contribute to reliable, scalable AI-powered applications. The role requires strong backend development, modern software practices, independent ownership, and practical use of AI coding assistants. The initial project is planned for two months, with potential extension.

Lead a squad of 8–20 engineers while remaining hands-on in frontend, backend, cloud, and AI development. Design domain-driven, event-driven architectures; build LLM-powered applications using Claude, AWS Bedrock, and LangGraph; translate Figma designs into accessible interfaces; establish engineering standards; manage CI/CD with GitHub Actions and AWS CDK; implement automated testing; and mentor engineers during agile delivery.

Lead discovery and rapid validation of an AI product initiative over a five-week freelance project. Responsibilities include customer interviews, prototype testing, hypothesis validation, requirements definition, prioritization, stakeholder communication, feasibility assessment, and go/no-go recommendations. The role works closely with software engineers, technical stakeholders, and 2–5 customer design partners to evaluate usability, business value, commercial potential, and integration readiness.

Design and build agentic AI platform capabilities, cloud-native enterprise applications, infrastructure, IaC, and CI/CD pipelines. Deploy and operate secure, governed solutions in regulated enterprise environments, integrate AI with legacy systems, and collaborate with architects and engineering leaders. The role requires strong software engineering, cloud engineering, agent platform development, technical leadership, and stakeholder management skills.

Implement and strengthen information security controls across CI/CD, APIs, endpoints, IAM, vulnerability management, and software supply chains. Build asset inventories and access matrices, integrate security scanning, enforce least privilege, manage secrets, support Qualys onboarding, coordinate remediation, document procedures, and collaborate with engineering, IT, and compliance teams. The role requires hands-on delivery, technical autonomy, strong English documentation, and knowledge of security frameworks and cloud environments.

Designs enterprise agentic AI architectures, evaluates platforms and buy-versus-build options, develops hands-on proofs of concept, and establishes secure, observable AgentOps/LLMOps lifecycles. The role requires integrating agents with APIs, MCP, and enterprise data, incorporating governance and AI risk controls, and converting prototypes into reusable production capabilities. The architect collaborates with senior stakeholders, provides decision-ready recommendations, and transfers knowledge through documentation, walkthroughs, and pairing.

Leads large, complex software programs for international clients with end-to-end accountability for delivery, budget, governance, risks, dependencies, change management, and stakeholder alignment. Manages distributed teams and external partners, mentors Delivery Managers, builds program teams, and ensures predictable delivery across scope, timelines, and contractual commitments. Requires initial work in India and frequent international travel thereafter.

Develop and maintain scalable PHP backend applications, databases, APIs, and cloud-based microservices. Responsibilities include implementing requirements, improving products, troubleshooting, testing, documentation, QA collaboration, and writing clean code. The role involves distributed multidisciplinary teamwork, mentoring, and knowledge sharing. Candidates need strong PHP 8+, MySQL, SQL, GraphQL, object-oriented programming, SOLID principles, design patterns, and unit and integration testing experience.