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Mid-level generalist Data Engineer, metro location, broad Azure/Databricks skillset increases applicant competition.
Core data engineering skills are transferable, though SAP Data Services and Azure specifics increase domain bias somewhat.
Required Azure/Databricks/ADLS skills and DevOps expectations create moderate technical filtering despite preferred years.
Design, develop, and test scalable data management and transformation pipelines using Microsoft Azure PaaS tools and DevOps methodologies.
Architect and manage data structures and pipelines enabling Data as a Service ensuring scalability, reliability, and performance.
Implement and manage DevOps pipelines and containerization to support continuous integration, deployment, and scalable cloud/edge solutions.
Bachelor’s degree in Computer Science, Software Engineering, Information Systems, or related field.
Experience working full systems development lifecycle with Agile methodologies.
Proficiency in Azure data management technologies including Azure ADF, ADLS, Databricks, SAP Data Services, SQL, and DevOps practices including containerization.
Work Experience Required: Not explicitly mentioned in the JD. Hybrid work required from Pune office (on-site 3 days/week).
Technically skilled in cloud-based data engineering with experience in Microsoft Azure ecosystem focusing on ADF, ADLS, Databricks, and SAP Data Services.
Experienced in collaborating with business stakeholders and cross-functional teams to deliver data-driven solutions and enable Data as a Service.
Comfortable working in hybrid model reporting to management and collaborating globally within Agile environment.