Senior Platform Engineer; AI & Analytics - Hybrid

Position: Senior Platform Engineer (AI & Analytics) - Hybrid
At Allianz Life, we are driven by our mission - we secure your future - and by our common goal of caring for tomorrow. We care for our employees by promoting an inclusive culture where everyone has the opportunity to grow and be rewarded for their success. We care for our customers by creating new products that help them protect their families and pursue their retirement goals.

We care for our community by giving time, resources, and donations. And we care for the future by supporting sustainability, protecting the local environment, and promoting equality in our communities.

What you do:

The Senior Platform Engineer will be a cross-disciplined, key role in driving Allianz Life's AI and Analytics capabilities on the Azure/Databricks platform. You'll leverage your hands-on data engineering, Dev Ops, and cloud expertise to build and maintain scalable cloud infrastructure and data pipelines that power advanced analytics and AI solutions. You'll have a hand in defining and execute the platform architecture with a focus on operational excellence, security, and performance.

Collaboration will be key, as you partner with IT, data science, analytics engineering, and vendor teams to operate a robust platform that accelerates innovation and business value.

Engineering & Operations (60%)

* Develop, deploy, and maintain platform components including data pipelines, Dev Ops pipelines, Kubernetes services, and various monitoring frameworks.

* Create and maintain templated project repositories enabled and simplified for teams with custom CLI.

* Ensure high availability, performance, and observability of platform services through proactive monitoring and incident response.

* Create/manage Terraform and Databricks DAB Infrastructure as Code repositories as needed.

Collaboration & Governance (30%)

* Partner with the internal team, IT, data science, and analytics engineering teams to support end-to-end solution delivery, including building and promoting data pipelines, provisioning infrastructure, and supporting Dev Ops pipelines and processes.

* Provide support and guidance across the SDLC, including CI/CD, release management, and environment promotion.

Innovation & Enablement (10%)

* Help evaluate emerging Azure and Databricks services and AI/ML capabilities to drive innovation and continuous improvement.

* Contribute to platform governance, including data ethics, compliance, and security best practices.

* Mentor technical teams and promote architectural standards and reusable patterns.

* Utilization of artificial intelligence tools and resources (e.g. generative AI)

What you bring:

* 6+ years of experience in a combination of Data Engineering, Dev Ops, and Cloud Engineering roles.

* Experience deploying infrastructure as code.

* Experience setting up and maintaining Kubernetes infrastructure for application development team

* Experience working with Azure resources in the context of resource provisioning, configuration, networking, monitoring, and maintenance.

* Experience working with Databricks (Lakehouse architecture, Spark, Unity Catalog, Delta tables).

* Experience with MLOps, Dev Ops, and SDLC practices in a regulated enterprise environment.

* Experience creating Git Hub Actions Workflows for code promotion across environments.

* Experience creating data ingestion and data transformation pipelines in Pyspark, preferably within Databricks.

* You must be legally authorized to work in the U.S. without requiring immigration sponsorship now or in the future. This includes holders of H-1B, H4, L-1, L-2, TN, OPT, CPT, and other nonimmigrant visas.

Job posting range $110,000 - $151,000

* For roles in zones 1 and 2: minimum zone 1 - mid zone 2

* For roles in zone 3: minimum zone 2 - mid zone 3

Note the job posting range is exclusive of company benefits or other compensation. This role is also eligible for an annual incentive program. If you are hired, your final base salary will be determined based on factors such as geographic location, experience, skills, competencies, and/or education. In addition to those factors, we will also consider internal equity of our current employees.

Please keep in mind that the range provided is the full…