Lead and mentor a team of platform engineers, fostering a culture of technical excellence, collaboration, and continuous improvement in building and maintaining cloud data solutions. Define the technical roadmap and strategy for the cloud data platform, leveraging Azure services such as Databricks, Storage Accounts, Virtual Machines, Azure Kubernetes Service (AKS), and Kafka, ensuring alignment with overall business objectives and data architecture principles. Collaborate extensively with Cloud Center of Excellence (CCoE), Information Security (InfoSec), Identity and Access Management (IAM), and Network teams to ensure the data platform adheres to best practices in security, compliance, governance, and operational efficiency. Oversee cloud cost monitoring, forecasting, and optimization for the Data and AI vertical, implementing strategies to maximize resource utilization and minimize expenditure across all cloud services. Evaluate and explore emerging technologies and services within Google Cloud Platform (GCP), including BigQuery, DataProc, Dataflow, and Google Kubernetes Engine (GKE), to identify opportunities for platform transformation, improved performance, and cost efficiencies. Establish and enforce engineering best practices, including CI/CD, automated testing, infrastructure as code (IaC), and monitoring frameworks, to ensure the reliability and maintainability of the data platform. Manage vendor relationships and evaluate new tools and technologies to enhance the capabilities and efficiency of the cloud data platform. Communicate complex technical concepts and strategies effectively to both technical and non-technical stakeholders, influencing decision-making and driving consensus. 20% domestic travel required. Must appear in office 2 days per week; WFH permissible 3 days per week.
Salary Range: $233,770 - $272,600
Employee pay will vary based on factors such as qualifications, experience, skill level, competencies and work location. We will meet minimum wage or minimum of the pay range (whichever is higher) based on city, county and state requirements.
1. Hands-On experience on specified technology stack - Azure Databricks, Containerization (Docker, Kubernetes), Kafka, SQL, NoSQL Databases in Azure, AWS or GCP cloud;
2. CI/CD practices and tools such as Jenkins, GitHub, Azure DevOps;
3. Data Warehousing, Data Lakes, Data Engineering, Data Science, Data Analytics, and Real-Time Data Streaming architectures;
4. Ability to collaborate effectively with various engineering partners to probe/ask questions, gather required information for cloud platform requirements, and participate as a value added cross-functional partner;
5. Knowledge of distributed data cloud platform with data governance, security, and compliance best practices;
6. Familiarity with Software Delivery LifeCycle, Agile and Scrum methodology; and
7. Cloud services cost, monitoring and optimization.
Bachelor’s degree or foreign degree equivalent in Computer Science, Computer Information Systems, Engineering, or related field and ten (10) years of progressive, post-baccalaureate experience in the job offered or a related role.
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