Azure Platform Engineer

Expert-level knowledge of hybrid and multi-cloud infrastructure (AWS, Azure, on-prem).

Extensive experience architecting large-scale distributed systems, focusing on performance, resilience, and scalability.

Deep expertise in DML operations across relational (Postgres, Oracle) and NoSQL (Cassandra) databases.

Advanced proficiency with Kafka and event streaming architectures, including schema registry management, replication, and consumer group design.

Mastery of caching architectures including distributed caching, multi-tier designs, and cache invalidation strategies.

Strong command of Infrastructure-as-Code and automation frameworks (Terraform, Ansible, CloudFormation).

Advanced scripting and orchestration using Python, Bash, or PowerShell.

In-depth understanding of observability, reliability, and data-driven automation at scale.

Solid grounding in networking, identity, and cloud security principles.

Proven leadership and influence across diverse engineering and architecture teams.

Strategic mindset with the ability to align technical direction with organizational business goals.

Exceptional communication and storytelling skills able to bridge technical and executive audiences.

Strong mentoring ability and commitment to developing engineering talent.

Operates with autonomy, foresight, and innovation in highly dynamic technical environments.

Architect and evolve hybrid and cloud platform architecture to support high performance, resiliency, and scalability.

Define platform modernization and migration strategies aligned with organizational goals and cloud transformation initiatives.

Influence architecture across teams driving adoption of microservices, event-driven integrations, and containerized workloads.

Establish standards for Infrastructure-as-Code, observability, and platform automation that enable secure and reliable delivery.

Define and lead the organizational strategy for DML operations across Postgres, Oracle, and Cassandra environments, ensuring efficient and secure data manipulation at scale.

Oversee the design, implementation, and optimization of DML logic, queries, and data pipelines, in alignment with Enterprise DDL governance and standards.

Architect Kafka-based event streaming systems that support high-throughput, real-time data movement and platform-level integrations.

Drive the adoption of event-driven design patterns for asynchronous communication and decoupled service architecture.

Define distributed caching strategies and frameworks (Redis, Memcached, or equivalent) to reduce latency, improve throughput, and optimize resource utilization.

Establish DML and data access best practices that balance performance, consistency, and reliability.

Lead enterprise-wide automation initiatives using Terraform, Ansible, or similar frameworks for consistent, repeatable infrastructure provisioning.

Oversee integration of data operations into CI/CD pipelines, ensuring robust testing, version control, and change governance.

Develop self-service frameworks and automation patterns that improve developer autonomy and reduce operational overhead.

Define and enforce platform security and governance standards for data access, messaging, and caching systems.

Collaborate with security teams to integrate compliance, encryption, and access controls into platform data operations.

Drive observability and reliability standards for data-intensive systems ensuring performance, fault tolerance, and cross-region resiliency.

Lead large-scale incident reviews, root-cause analysis, and resilience engineering initiatives for platform-wide stability.

Serve as a senior technical mentor for Platform Engineers and cross-functional teams, providing guidance on architecture, data operations, and cloud design.

Partner with product, security, and enterprise architecture leaders to align technical strategy with business outcomes.

Influence investment and roadmap decisions for platform modernization and automation initiatives.

Represent platform engineering in organizational architecture councils and leadership forums.

Drive exploration and adoption of emerging technologies including streaming analytics, AI-driven automation, and next-gen data caching strategies.

Encourage experimentation and continuous improvement across platform engineering practices.

Contribute to thought leadership and knowledge sharing across engineering communities.

For applications and inquiries, contact:View email address on click.appcast.io