Data Engineer - INTL India - 94b043a3

Required Skills & Experience

Skills

· 5+ years of experience in hands-on development in cloud-based solutions. (Azure, AWS) · 5+ years of experience with Azure including Azure Data Factory, Azure Synapse, Azure Data Lake Storage, SQL DW, COSMOS DB, Azure Functions, Serverless Architecture, ARM Templates · 5+ years of hands-on knowledge on Azure Databricks development using SQL and Python languages is required. · Hands on experience in Performance tuning and optimizing code running in Databricks environment. · Designing and building of ETL data pipelines using Azure tools. · Knowledge of Dev-Ops processes (including CI/CD) in Azure or Git hub is essential. · Nice-to-have experience in additional ERP Platforms such as Dynamics D365 or SAP. · Working knowledge of Logic apps, Stream Analytics, Analysis Services, Service Bus, Log Analytics is desirable. · Experience in translating business requirements to user stories in Agile and implement solutions in agile method is desirable. · The ability to automate tasks and deploy production standard code (with unit testing, continuous integration, versioning etc.) Excellent Communication skills to work with different hierarchy of the organization.

Job Description

We are seeking an experienced Data Engineer to design, develop, and optimize cloud-based data solutions within the Azure ecosystem. This role will focus heavily on building scalable data pipelines, integrating data from multiple sources, and developing solutions using Azure Databricks, Azure Data Factory, SQL, and Python. The Data Engineer will partner with cross-functional engineering teams to support data ingestion, processing, integration, and transformation while delivering production-ready solutions in an Agile environment.

Job Responsibilities.

· Analyze, design, build and implement Azure solutions using Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure Logic Apps. · Design and implement data ingestion techniques from multiple sources using Azure Databricks. · Partner with Data Engineering experts and contribute in areas such as data access & ingestion, data processing, data integration and data transformation. · Actively participate in daily standup, sprint planning meetings, and demos in an Agile Model · Partner with multiple teams across company hierarchy and work in a self-driven, dynamic, fast-track matrix environment. · Execute against a backlog of User Stories and tasks on Jira. Maintain best practice standards for the development or cloud-based solutioning.