Platform Architect-Data Platforms

About the role

We are seeking a highly skilled Platform Engineering Lead to architect, build, and manage enterprise-scale cloud-native data platforms supporting Asset Management business functions. The role will lead platform engineering, infrastructure automation, DevOps enablement, platform reliability, security, and operational excellence across the Enterprise Data Office (EDO). The ideal candidate will have deep expertise in Databricks, dbt, AWS Cloud, Terraform, Python, DevOps, Platform Engineering, and Data Operations, with strong experience supporting investment management organizations.

Responsibilities

• Lead the design, implementation, and management of enterprise data platforms.
• Define platform engineering strategy aligned with EDO and enterprise architecture standards.
• Establish reusable platform frameworks, accelerators, and engineering best practices.
• Drive cloud-native modernization initiatives across data and analytics ecosystems.
• Own platform lifecycle management, scalability, availability, and reliability.
• Lead enterprise-wide Databricks platform architecture and administration.
• Design and implement Lakehouse architecture leveraging Delta Lake.
• Manage Databricks Workflows, Delta Live Tables (DLT), Unity Catalog, MLflow, Structured Streaming, Cluster Policies, Security and Access Controls.
• Optimize platform performance and cost efficiency.
• Build governance controls across development, test, and production environments.
• Lead cloud engineering activities using AWS services: S3, ECS, EKS, Lambda, Glue, CloudWatch.
• Build reusable Terraform modules, automate environment provisioning, and implement infrastructure standardization and governance.
• Maintain infrastructure version control and ensure compliance through Infrastructure-as-Code practices.
• Design and implement CI/CD pipelines using GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, Terraform, Docker, and Kubernetes.
• Automate deployment and release management processes, enabling Infrastructure-as-Code and GitOps methodologies.
• Improve deployment velocity and reliability.
• Support engineering teams with self-service platform capabilities.
• Support API integrations and operational workflows.
• Establish Site Reliability Engineering (SRE) practices, defining platform SLAs, SLOs, and operational metrics.
• Lead platform monitoring, observability, and incident management.
• Drive root cause analysis and preventive actions.

Requirements

• Deep expertise in Databricks, dbt, AWS Cloud, Terraform, Python, DevOps, Platform Engineering, and Data Operations.
• Strong experience supporting investment management organizations.
• Experience with PySpark and Airflow (Astronomer is a plus).

Pay

$150,000 - $240,000 a year