ppBe among the first 25 applicants. /p pDirect message the job poster from Virtusa. /p pLocation: Barcelona, Spain. Contract role. /p pHybrid 3 days a week from office. /p h3Job summary /h3 pWe are seeking a hands‑on AI Platform Engineer to design, build, and operate Databricks‑based data and AI platforms on AWS. You will enhance AI capabilities by leveraging Databricks (Workspace, Unity Catalog, Lakehouse, MLflow), modern cloud services, and DevOps/MLOps practices to deliver reliable, secure, and scalable platforms. /p h3About the role /h3 pAs an AI Platform Engineer, you will invent and industrialize how the Project team uses Databricks, machine learning, and data. You will build, deploy, and evolve next‑generation platform capabilities at scale, partnering with data scientists, ML engineers, and platform teams to deliver a best‑in‑class developer experience on the Lakehouse. /p h3What candidate is needed /h3 ul liProficient in cloud operations on AWS, with strong understanding of scaling infrastructure and optimizing cost/performance. /li liProven hands‑on experience with Databricks on AWS: workspace administration, cluster and pool management, job orchestration (Jobs/Workflows), repos, secrets, and integrations. /li liStrong experience with Databricks Unity Catalog: metastore setup, catalogs/schemas, data lineage, access control (ACLs, grants), attribute‑based access control, and data governance. /li liExpertise in Infrastructure as Code for Databricks and AWS using Terraform (databricks and aws providers) and/or AWS CloudFormation; experience with Databricks asset bundles or CLI is a plus. /li liExperience implementing CI/CD and GitOps for notebooks, jobs, and ML assets using GitHub and GitHub Actions (or GitLab/Jenkins), including automated testing and promotion across workspaces. /li liAbility to structure reusable libraries, package and version code, and enforce quality via unit/integration tests and linting. Proficiency with SQL for Lakehouse development. /li liExperiment tracking, model registry, model versioning, approval gates, and deployment to batch/real‑time endpoints (Model Serving). /li liAWS IAM/STS, PrivateLink/VPC, KMS encryption, Secrets, SSO/SCIM provisioning, and monitoring/observability (CloudWatch/Datadog/Grafana).



/li liExperience with DevOps practices to enable automation strategies and reduce manual operations. /li liExperience or awareness of MLOps practices; building pipelines to accelerate and automate machine learning will be viewed favorably. /li liExcellent communication, cross‑functional collaboration, and stakeholder management skills. /li liDetail‑oriented, proactive, able to work independently and within a distributed team. /li /ul h3What candidate will do /h3 ul liDesign and implement scalable Databricks platform solutions to support analytics, ML, and GenAI workflows across environments (dev/test/prod). /li liAdminister and optimize Databricks workspaces: cluster policies, pools, job clusters vs. all‑purpose clusters, autoscaling, spot/fleet usage, and GPU/accelerated compute where applicable. /li liImplement Unity Catalog governance: define metastores, catalogs, schemas, data sharing, row/column masking, lineage, and access controls; integrate with enterprise identity and audit. /li liBuild IaC for reproducible platform provisioning and configuration using Terraform; manage config‑as‑code for cluster policies, jobs, repos, service principals, and secret scopes. /li liImplement CI/CD for notebooks, libraries, DLT pipelines, and ML assets; automate testing, quality gates, and promotion across workspaces using GitHub Actions and Databricks APIs. /li liStandardize experiment structure, implement model registry workflows, and deploy/operate model serving endpoints with monitoring and rollback. /li liDevelop and optimize Delta Lake pipelines (batch and streaming) using Auto Loader, Structured Streaming, and DLT; enforce data quality and SLAs with expectations and alerts. /li liOptimize cost and performance: rightsize clusters and pools, enforce cluster policies and quotas, manage DBU consumption, leverage spot/fleet,



and implement chargeback/showback reporting. /li liIntegrate observability: metrics/logs/traces for jobs, clusters, and model serving; configure alerting, on‑call runbooks, and incident response to reduce MTTR. /li liEnsure platform security and compliance: VPC design, PrivateLink, encryption at rest/in transit, secrets management, vulnerability remediation, and audit readiness; align with internal security standards and, where applicable, GxP controls. /li liCollaborate with cross‑functional teams to integrate the Databricks platform with data sources, event streams, downstream applications, and AI services on AWS. /li liConduct technical research, evaluate new Databricks features (e.g., Lakehouse Federation, Vector Search, Mosaic AI), and propose platform improvements aligned to roadmap. /li liRegularly communicate progress, risks, and recommendations to client managers and development teams. /li /ul h3Required qualifications /h3 ul liHands‑on Databricks administration on AWS, including Unity Catalog governance and enterprise integrations. /li liStrong AWS foundation: networking (VPC, subnets, SGs), IAM roles and policies, KMS, S3, CloudWatch; EKS familiarity is a plus but not required for this Databricks‑focused role. /li liProficiency with Terraform (including databricks provider), GitHub, and GitHub Actions. /li liStrong Python and SQL; experience packaging libraries and working with notebooks and repos. /li liExperience with MLflow for tracking and model registry; experience with model serving endpoints preferred. /li liFamiliarity with Delta Lake, Auto Loader, Structured Streaming, and DLT. /li liExperience implementing DevOps automation and runbooks; comfort with REST APIs and Databricks CLI. /li liGit and GitHub proficiency; code review and branching strategies. /li /ul h3Seniority level /h3 ul liMid‑Senior level /li /ul h3Employment type /h3 ul liContract /li /ul h3Job function /h3 ul liAnalyst /li /ul h3Industries /h3 ul liIT Services and IT Consulting and Data Infrastructure and Analytics /li /ul pReferrals increase your chances of interviewing at Virtusa by 2x. /p pGet notified about new Platform Engineer jobs in bBarcelona, Catalonia, Spain /b. /p /p #J-18808-Ljbffr

📌 AI platform Engineer (Barcelona)
🏢 Virtusa
📍 Barcelona