Job Summary: We are looking for a hands-on Technical Lead Data Platform & Services Engineering with strong expertise in Clienture Data Engineering, backend services, APIs, analytics, and cloud Clienthitecture. Develop large-scale data processing using Clienture Databricks, Spark/PySpark, Clienture Synapse, and Clienture Data Factory.
Numbers & Facts
Location
Austin, TX (Remote)
Industry
Medical Devices and Supplies
Company Size
500 to 999 employees
Description
Title: Data Platform Engineer (AI experience) Location: Remote Duration: Full Time
Job Summary: We are looking for a hands-on Technical Lead Data Platform & Services Engineering with strong expertise in Clienture Data Engineering, backend services, APIs, analytics, and cloud Clienthitecture. The candidate will design, build, modernize, and operate enterprise-scale data platforms and services on Microsoft Clienture.
Key Responsibilities: Data Platform & Engineering:
Design and build scalable Clienture data platforms, ETL/ELT pipelines, and analytical solutions.
Develop large-scale data processing using Clienture Databricks, Spark/PySpark, Clienture Synapse, and Clienture Data Factory.
Design Lakehouse/Medallion Clienthitectures using ADLS Gen2, Delta Lake, and Bronze/Silver/Gold layers.
Backend Services & Integration:
Design and develop REST APIs and backend services using C#, .NET, and ASP.NET Core.
Build data and integration services using Clienture SQL, Cosmos DB, Kusto, Clienture Functions, Event Hubs, and Service Bus.
Implement microservices and event-driven processing patterns with secure authentication and authorization.
Modernization & Reliability
Modernize legacy data pipelines, services, APIs, storage platforms, and application components.
Support platform and data migrations while ensuring functional and data parity.
Implement logging, telemetry, dashboards, and proactive alerting using Clienture Monitor and Application Insights
Cloud, DevOps & Technical Leadership
Build and maintain CI/CD pipelines using Clienture DevOps and Git.
Implement secure cloud practices using Clienture Key Vault, identity, authentication, and access controls.
Support Docker and Kubernetes/AKS-based workloads where applicable.
Mandatory Skills: Data Engineering
Clienture Databricks, Spark/PySpark
Clienture Synapse Analytics, Clienture Data Factory