What are the responsibilities and job description for the Data Platform Engineer position at MW Partner?
MW Partners is currently seeking a Data Platform Engineer to work for our client who is a global leader in multimedia and creativity software products.
Responsibilities and duties:
- Setup and maintain production scale Databricks environment on public cloud such as Microsoft Azure and AWS (Amazon Web Services)
- Setup and maintain production scale data storage such as ADLS (Azure Data Lake Storage) and AWS S3 for multiple tenant teams using our Data Platform
- Setup and maintain production scale micro services to support the daily operation of our data platform. Services include job scheduling, security, financial, and administrative services, etc.
- Provide triage and guidance to the team on various support issues raised by our tenants
- Develop tools and automation solutions for configuration management, service deployments, monitoring, and alerting to assist with daily RTB (Running the Business) operations
- Budget and monitor cloud spend, always think of ways to avoid cloud resource wastage, utilize 3rd party tools, or develop your own tools to help the team with cost optimization
- Assure security and privacy compliance and implement Client Security & Compliance solutions to lock down data stored in our data lake
- Explore GenAI technologies and find opportunity to integrate them with our data platform, providing platform enhancement or improving platform user experience in the end
- Work with various 3rd party vendors for troubleshooting, proof of concept, and other collaborative projects to enhance our product.
Requirements:
- BS in Computer Science, Computer Engineering, or similar
- Cloud Infrastructure Administration and Automation: AWS, Azure
- Proficient with following storage technologies: ADLS Gen2, AWS S3, Hive or MySQL, MongoDB, Vector Databases
- Setup, troubleshoot and maintain following technologies: Databricks Workspace, includes but not limited to Unity Catalog, Vector Search, SQL Warehouse, Serverless Compute, Spark workloads, Airflow and DAGs, Azure Kubernetes Service or Elastic, Kubernetes Service, Collibra, Neo4J, Metric Insights
- Ability to setup monitoring and alerting with: Databricks System Tables, Prometheus, Splunk, ELK, PowerBI
- Familiar with how to troubleshoot and maintain: Servers with Linux system, Kubernetes environment
- Knowledge to operate with: Jira, Service Now
For a confidential discussion or to find out more, contact Rucha Swain on 909- 235- 9478 or apply now.
Salary : $134,200 - $161,100
