Jobs / India / Robert Bosch LLC
Senior Data Scientist – AI, Data Engineering & Intelligent Automation
Robert Bosch LLC · 🌍 bangalore, IN
Sponsorship verdict
No sponsorship evidence yet
No government record and no wording either way. Not a refusal — ask the recruiter.
- No government sponsor record hereNo government sponsor record covers this employer in this country.
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- Can’t check pay against the visa rulesWe don’t have visa salary rules for this country yet.
- Confirmed live todayWhen a source last listed this job as open.
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Why not apply?
No register record and no sponsorship wording in the posting. Worth asking the employer before investing significant time.
SponsorApply flags time-wasters so your applications go where they can land. These come from the posting's own wording — read the original listing to confirm. See better-fit alternatives →
Sponsor Radar — Robert Bosch LLC
No government sponsor record covers this employer in this country.
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Robert Bosch LLC →
About the role
Key ResponsibilitiesData Analytics/Pyspark/Azure data bricksPipeline Design & Development: Build, monitor, and maintain robust, scalable batch and real-time ETL/ELT pipelines using PySpark, SQL, Delta Lake, and Auto Loader.Data Governance & Security: Enforce data access policies, row/column-level security, and lineage tracking using Databricks Unity Catalog to protect PII and maintain complianceOrchestration & Workflow Automation: Schedule and orchestrate multi-task jobs using Databricks Workflows (Lakeflow Jobs) or external schedulers (e.g., Apache Airflow, Azure Data Factory)Data Quality Assurance: Define and integrate automated data quality rules, validation checks, and testing frameworks (e.g., Great Expectations, Delta Live Tables expectations) directly into pipelinesBig Data handling :Design and implement scalable data ingestion, transformation, and processing pipelines.Automate data collection, validation, and integration workflows.Ensure data quality, reliability, and governance across the data ecosystem.Interface with diverse enterprise data sources including databases, APIs, cloud platforms, files, streaming systems, and third-party applications.Analyze structured and unstructured data to derive actionable insights and recommendations.Design experiments, evaluate data performance, and continuously improve solution effectiveness.Apply advanced analytics techniques to support business decision-making.Data Visualization & Business InsightsBuild intuitive dashboards and visualizations to communicate insights effectively.Translate technical findings into business-friendly recommendations.Support leadership teams with data-driven decision-making.AI, GenAI & Agentic SolutionsDesign and develop AI-powered applications using modern Large Language Models (LLMs).Build Agentic AI workflows and intelligent assistants for enterprise use cases.Implement Model Context Protocol (MCP)-based integrations and orchestration frameworks.Develop Retrieval-Augmented Generation (RAG) and enterprise knowledge solutions.Deployment, Cloud & InfrastructureDeploy AI and analytics solutions across cloud and on-premises environments.Design scalable solution architectures on Azure, AWS, GCP, or hybrid platforms.Containerize applications using Docker.Collaborate with infrastructure and DevOps teams to ensure production-grade deployments.Stakeholder Management & Technical LeadershipWork closely with business stakeholders to understand requirements and define solution roadmaps.Lead technical discussions and provide architectural guidance.Present complex technical concepts to both technical and non-technical audiences.Mentor junior team members and promote engineering best practices. Required Technical SkillsData Science & AnalyticsMachine LearningStatistical ModelingPredictive AnalyticsData MiningFeature EngineeringModel Evaluation and OptimizationProgramming & DevelopmentPython (Mandatory)SQL (Mandatory)Strong scripting and automation skillsREST APIs and system integrationsVersion control systems (Git)Data EngineeringETL/ELT DevelopmentData Pipeline DesignData Warehousing ConceptsWorkflow AutomationStructured and Unstructured Data ProcessingData VisualizationPower BI, Tableau, Looker, or equivalent platformsDashboard DevelopmentData StorytellingCloud & InfrastructureAzure, AWS, or GCPDockerKubernetesCI/CD ConceptsSolution Deployment and MonitoringAI & Generative AILarge Language Models (LLMs)Claude, OpenAI, and related AI platformsAgentic AI FrameworksModel Context Protocol (MCP)Prompt EngineeringRAG ArchitecturesAI Application DeploymentQualificationsBachelor's Degree (BE/BTech) in Computer Science, Information Technology, Data Science, Engineering, Mathematics, Statistics, or a related field.Master's Degree is an added advantage.8+ years of experience i