Bosch Group
Senior Data Scientist – AI, Data Engineering & Intelligent Automation
- Compensation
- Not disclosed
- Location
- bangalore, in
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 6+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Bachelor'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 acquisition
Full description
Job Description
Key Responsibilities:
- Data Analytics/Pyspark/Azure data bricks
- Pipeline 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 compliance
- Orchestration & 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 pipelines
- Big 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 Insights. Build 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 Solutions.
- Design 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 & Infrastructure Deploy 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 Leadership. Work 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.