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Architect - Data Engineer

10 - 15 years

32 - 35 Lacs

Posted:1 week ago| Platform: Naukri logo

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Full Time

Job Description

Responsibilities Lead the migration and modernization of data platforms, moving applications and pipelines to Azure-based solutions. Actively contribute to code development in projects and services. Manage and scale data pipelines from internal and external data sources to support new product launches and ensure high data quality. Develop automation and monitoring frameworks to capture key metrics and operational KPIs for pipeline performance. Implement best practices around systems integration, security, performance, and data management. Collaborate with internal teams, including data science and product teams, to drive solutioning and proof-of-concept (PoC) discussions. Develop and optimize procedures to transition data into production. Define and manage SLAs for data products and operational processes. Prototype and build scalable solutions for data engineering and analytics. Research and apply state-of-the-art methodologies in data and Platform engineering. Create and maintain technical documentation for knowledge sharing. Develop reusable packages and libraries to enhance development efficiency. Qualifications Bachelors degree in Computer Science, MIS, Business Management, or related field 10 + years experience in Information Technology 4 + years of Azure, AWS and Cloud technologies Experience in data platform engineering, with a focus on cloud transformation and modernization. Strong knowledge of Azure services, including Databricks, Azure Data Factory, Synapse Analytics, and Azure DevOps (ADO). Proficiency in SQL, Python, and Spark for data engineering tasks. Hands-on experience building and scaling data pipelines in cloud environments. Experience with CI/CD pipeline management in Azure DevOps (ADO). Understanding of data governance, security, and compliance best practices. Experience working in an Agile development environment. Prior experience in migrating applications from legacy platforms to the cloud. Knowledge of Terraform or Infrastructure-as-Code (IaC) for cloud resource management. Familiarity with Kafka, Event Hubs, or other real-time data streaming solutions. Experience with lagacy RDBMS (Oracl, DB2, Teradata) Background in supporting data science models in production.

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