Senior Data Scientist AI Data Engineering And Intelligent Automation

Bosch; Bengaluru; On-site; INR 3,000,000 - 5,500,000; Full time

Job summary

Bosch Global Software Technologies Private Limited seeks an experienced Data Engineer to design robust batch and real-time ETL/ELT pipelines using PySpark, SQL, Delta Lake, and Auto Loader. You will enforce data governance, security, and lineage with Unity Catalog, and orchestrate jobs via Databricks Workflows or Airflow/Azure Data Factory.

The role emphasizes data quality, scalable ingestion, and translating insights into business actions, including AI-powered workflows and agentic solutions.

Qualifications

• Bachelor’s degree in a relevant field; Master’s an advantage.
• 8+ years experience in Data Science, Data Engineering, AI or Analytics.
• Proven track record delivering end-to-end data solutions.

Responsibilities

• Design and build scalable ETL/ELT pipelines with PySpark, SQL, and Delta Lake.
• Governance, security and lineage tracking using Databricks Unity Catalog.
• Orchestrate workflows with Databricks Workflows or external schedulers.
• Develop AI-powered solutions and integrate LLM-based workflows.
• Collaborate with stakeholders to translate data insights into actions.

Skills

Python

SQL

PySpark

Delta Lake

Databricks

Airflow

Azure Data Factory

Git

Education

BE/BTech in CS/IT/Data Science

Master's degree (advantage)

Tools

Databricks

Docker

Kubernetes

Job description

Job Description:

Company Description

Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

Job Description

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 in Data Science, Data Engineering, AI, or Analytics domains.Proven experience delivering end-to-end solutions from data acquis

Qualifications

B.E

Additional Information

6 to 8 years

Requirements: