The company is looking to define and implement a data observability and resiliency strategy for its data platform, aiming to improve data management, engineering practices, and align initiatives with business goals.
Requirements
- architecting and developing multi- tier applications using Java and Python
- working with AWS Stack including VPC, ECS, EKS, Data Lake, CloudWatch, CloudTrail, Lambda, EMR, Glue, and Athena building cutting-edge applications on cloud
- networking on AWS implementing solutions using Transit Gateway and NACLs
- building containerized applications using Kubernetes and Elastic Container on AWS
- working with cloud native design patterns, cloud migration patterns, mainframe migration, hybrid migration workloads, function as a service (FaaS), and microservices
- using multi-cloud providers like Azure, Aws, Pivotal Cloud Foundry, and Google Cloud for both transactional and data-intensive applications
- working with hybrid observability stack using frameworks and platforms including Datadog, Splunk, Grafana, and Dynatrace to implement logging, metrics, and alerts management
Responsibilities
- Define and implement the data observability and resiliency strategy for the company's data platform.
- Strategize and implement resiliency across Data Asset, Platform, and consumer-specific resiliency by enabling Cross Account Cross Regions (CACR) S3 replications, AWS Lake formation cross-regional backup, Glue Catalog cross-regional backup, and applications HA setup.
- Design the architecture and oversee the implementation of the observability across data platforms.
- Guide the team to build Hybrid Cloud Applications and scalable, secure, and cost-efficient Splunk-based Logging and Tracing, and enable applications that support data ecosystems on AWS.
- Enable networking across services.
- Monitor system performance and implement proactive measures to ensure reliability.
- Implement best practices for data governance, security, and compliance.
Other
- Lead and mentor a team of Cloud Engineers/Architects and Operations Engineers
- Collaborate with senior leadership to align data lake and pipeline initiatives with business goals while driving innovation and best practices in data management and engineering.
- Manage project timelines, resources, and budgets.
- Coordinate with cross-functional teams to ensure seamless integration and deployment.
- Oversee recruitment, training, and performance evaluations for the team.
