Senior Data Scientist – AI, Data Engineering & Intelligent Automation

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 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 data collection validation and integration data quality reliability and governance across the data with diverse enterprise data sources including databases APIs cloud platforms files streaming systems and third-party structured and unstructured data to derive actionable insights and experiments evaluate data performance and continuously improve solution advanced analytics techniques to support business Visualization & Business InsightsBuild intuitive dashboards and visualizations to communicate insights technical findings into business-friendly leadership teams with data-driven GenAI & Agentic SolutionsDesign and develop AI-powered applications using modern Large Language Models (LLMs).Build Agentic AI workflows and intelligent assistants for enterprise use Model Context Protocol (MCP)-based integrations and orchestration Retrieval-Augmented Generation (RAG) and enterprise knowledge Cloud & InfrastructureDeploy AI and analytics solutions across cloud and on-premises scalable solution architectures on Azure AWS GCP or hybrid applications using with infrastructure and DevOps teams to ensure production-grade Management & Technical LeadershipWork closely with business stakeholders to understand requirements and define solution technical discussions and provide architectural complex technical concepts to both technical and non-technical 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 DeploymentQualificationsBachelors Degree (BE/BTech) in Computer Science Information Technology Data Science Engineering Mathematics Statistics or a related Degree is an added advantage.8 years of experience in Data Science Data Engineering AI or Analytics experience delivering end-to-end solutions from data acquisit

Qualifications :

B.E

Additional Information :

6 to 8 years

Remote Work :

No

Employment Type :

Full-time