Data Engineer

• Architect, design, and implement end-to-end data solutions using Azure Databricks, PySpark, Azure Data Factory, and Azure SQL
• Design, build, and maintain data pipelines from data sources through integration to consumption
• Implement data modeling standards across bronze, silver, and gold data lake layers
• Develop conceptual, logical, and physical data models
• Optimize Spark and SQL workloads for performance, scalability, and cost efficiency
• Manage metadata using data preparation, integration, and AI-enabled tools
• Drive automation of data integration and repeatable data preparation tasks
• Build REST/JSON API integrations and real-time ingestion frameworks
• Automate workflows using Azure DevOps pipelines and Git-based CI/CD
• Implement reusable pipeline templates for ingestion and transformation
• Develop automated unit, regression, and integration testing frameworks
• Prepare and curate datasets for BI, reporting, and advanced analytics
• Partner with analytics teams to define semantic models and KPIs
• Implement performance-optimized models for self-service analytics
• Support end users with data visualization solutions when needed
• Lead technical design reviews and mentor junior engineers
• Gather and refine data requirements with cross-functional groups, business analysts, and stakeholders
• Collaborate with business and IT stakeholders to align data engineering with organizational objectives
• Contribute to architectural roadmaps and technology evaluations
• Identify inefficiencies and recommend improvements to the executive team

Senior Data Engineer – India

• Partner with the Product Solutions team and business stakeholders across Warner Music Group
• Rapidly build and deploy automation and data- and AI-driven solutions
• Work directly with key stakeholders across labels and global functions
• Translate stakeholder pain points into workflows that reduce tasks from weeks to minutes
• Deliver full-stack solutions including data pipelining and interoperability
• Develop backend systems in Python
• Develop dashboards and Streamlit applications
• Leverage Databricks and Snowflake AI tools such as Genie and Cortex
• Establish system frameworks, operational playbooks, and technical guidelines
• Contribute reusable implementations to internal marketplace assets
• Align solutions with the Data and Insights engineering roadmap

Senior Forward Deployed Engineer, Data & AI

• Build and operate pipelines, integrations and the warehouse supporting valuation and monitoring
• Own production pipelines from source capture through transformation, reconciliation and client delivery
• Put production pipelines under GitHub, automated testing and CI/CD
• Help redefine platform architecture across ingestion, processing and delivery
• Build and operate batch and streaming pipelines from databases, APIs, event streams and semi-structured sources
• Implement change data capture and incremental loading, including ordering, deletes, replay and slowly changing dimensions
• Build medallion datasets and dimensional models for Snowflake, Microsoft SQL Server and Databricks
• Apply data contracts, reconciliation and row-level quarantine before publication
• Own GitHub workflow and CI/CD, including tests, reviews, environment promotion and deployment as code
• Investigate production data failures and translate product, valuation and client-facing requirements into operable pipelines

Senior Data Engineer

• Design, develop, and maintain scalable data pipelines using Microsoft Azure Fabric
• Build reliable ETL/ELT processes for structured and unstructured data
• Work with business teams to understand data requirements and translate them into technical solutions
• Optimize data processing workflows for performance, scalability, and cost
• Apply AI-assisted development tools and modern engineering practices to improve delivery speed and solution quality
• Troubleshoot production issues and proactively identify improvements
• Collaborate with architects, analysts, and developers throughout the project lifecycle
• Take responsibility for quality, timelines, and outcomes without constant follow-up
• Use AI and automation to solve problems, improve engineering productivity, and deliver better solutions
• Raise risks early, ask questions when something isn't clear, and keep stakeholders informed
• Adjust priorities while maintaining delivery commitments

• Design scalable data solutions
• Build robust data pipelines
• Model enterprise datasets
• Enable analytics and AI/ML use cases on Palantir Foundry
• Perform data ingestion, pipeline building and transformations
• Build interactive applications using Foundry Workshop, Slate and custom TypeScript frontends
• Deliver complex data engineering solutions in agile environments

• Design and build scalable, production-grade data engineering solutions using the Databricks Lakehouse Platform
• Develop client-focused Proof of Concepts (POCs) demonstrating modern data engineering and analytics capabilities
• Translate business and analytical requirements into robust data models and layered architectures (Bronze/Silver/Gold)
• Design robust data ingestion, transformation, and orchestration pipelines using Databricks best practices
• Implement enterprise-grade data governance, security, and access control using Unity Catalog and related Databricks capabilities

Assistant Manager – Data Engineer

• Design and implement scalable data architectures for supply chain data platforms, analytics, reporting, and downstream applications
• Define enterprise data models, logical and physical data structures, data domains, and data integration patterns
• Architect cloud-based data solutions using Microsoft Azure services
• Design and optimize data processing and analytics solutions using Databricks, including data lakehouse architecture and distributed data processing
• Collaborate with data engineering teams on data ingestion, transformation, storage, orchestration, and consumption best practices
• Translate complex business and technical requirements into architecture and solution designs
• Establish standards for data quality, metadata management, lineage, security, access control, and governance
• Work with cross-functional stakeholders to understand supply chain processes and identify data modernization and optimization opportunities
• Review existing data platforms and recommend improvements to architecture, performance, scalability, and maintainability
• Provide technical leadership and architectural guidance to data engineers and development teams
• Create architecture diagrams, technical documentation, data models, and solution design specifications
• Ensure alignment with enterprise architecture, cloud security, compliance, and data governance standards

Data Architect – Supply Chain

• Design, develop, and maintain scalable data engineering solutions using Python, SQL, and Snowflake
• Build and optimize ETL/ELT pipelines for large-scale structured and unstructured datasets
• Develop modern web applications and data-driven interfaces using React
• Leverage Generative AI and LLM integrations to solve business problems and improve operational efficiency
• Participate in Agile sprint planning, stand-ups, retrospectives, and code reviews
• Design and implement Snowflake data architectures, including Tasks, Streams, Dynamic Tables, and performance optimization
• Collaborate with business stakeholders to understand requirements and deliver scalable, data-driven solutions
• Implement CI/CD pipelines and DevOps best practices for application and data platform deployments
• Establish coding standards, testing strategies, monitoring, and data governance practices
• Mentor junior developers and provide technical leadership across projects
• Analyze business and customer data to generate insights for decision-making and audience targeting initiatives
• Work with Product, Analytics, AI, and Engineering teams to deliver end-to-end solutions

• Build and maintain data pipelines to transform, process, and ingest wind measurement and master data from multiple sources and formats
• Develop and optimize data models and schemas for storing and retrieving structured and unstructured data
• Analyze and troubleshoot data pipelines and infrastructure issues
• Implement data quality and governance processes to ensure data accuracy, consistency, and reliability

• Design, build and operate a secure, scalable, AI-ready data and analytics platform on Microsoft Azure and Microsoft Fabric
• Administer and optimize Azure and Fabric platform resources, subscriptions, resource groups, RBAC, Azure Policies, Fabric capacities, workspaces, gateways and item governance
• Manage storage and compute layers across Fabric OneLake, ADLS Gen2, Delta Lake, Lakehouse/Warehouse, SQL pools, Spark runtime and capacity settings
• Enable and operate data ingestion and transformation services using Fabric Spark Notebooks and Materialized Lake Views
• Establish platform reliability through monitoring, alerting, autoscaling, performance tuning, cost control, tagging, chargeback/showback and capacity optimization
• Harden end-to-end platform security using Entra ID, PIM, conditional access, managed identities, Key Vault, private endpoints, encryption and network isolation
• Implement governance, compliance and data protection controls using Microsoft Purview, DLP, sensitivity labels, retention policies and auditing
• Enable AI/ML and advanced analytics workloads by integrating Azure Machine Learning and Fabric ML experiences
• Oversee CI/CD and lifecycle management for analytics and data platform artifacts using Fabric Git integration and GitHub Enterprise Cloud
• Act as tenant and workspace administrator and platform enabler for Fabric and Power BI
• Collaborate cross-functionally, define best practices and coach teams on platform usage
• Stay current with emerging technologies and industry trends to enhance platform engineering processes and technologies

Data Engineer jobs in India

Senior Data Engineer – India

Senior Forward Deployed Engineer, Data & AI

Senior Data Engineer

Senior Data Engineer

Data Engineer

Assistant Manager – Data Engineer

Data Architect – Supply Chain

Data Engineer

Data Engineer

Senior Data Platform Administrator