Data Platform Engineering Lead (1147943)

The Judge Group; Tustin (CA); On-site; USD 160,000 - 170,000; Full time

Job summary

The Judge Group is seeking a Data Platform Engineering Lead to architect, build, and manage enterprise-scale cloud-native data platforms supporting Asset Management functions. The role leads platform engineering, automation, DevOps enablement, platform reliability, security, and operational excellence across the Enterprise Data Office.

Ideal candidate will have deep expertise in Databricks, dbt, AWS Cloud, Terraform, Python, DevOps, Platform Engineering, and Data Operations, with strong

Qualifications

• Deep expertise in Databricks, dbt, AWS Cloud, Terraform, Python, DevOps, Platform Engineering, and Data Operations.
• Strong experience supporting investment management organizations.
• Ability to architect, build and manage enterprise-scale cloud-native data platforms.

Responsibilities

• Lead design, implementation, and management of enterprise data platforms.
• Define platform engineering strategy aligned with standards.
• Establish reusable platform frameworks, accelerators, and best practices.
• Drive cloud-native modernization across data and analytics ecosystems.
• Own platform lifecycle, scalability, availability, and reliability.
• Lead Databricks platform architecture and administration.

Skills

Data Bricks

EBT

Airflow

Asset Management exp

Tools

Databricks

dbt

AWS Cloud

Terraform

Python

DevOps

Platform Engineering

Data Operations

Docker

Kubernetes

Job description

Location: Tustin, CA

Location: Irvine, CA

Salary: $160,000.00 USD Annually - $170,000.00 USD Annually

Contract type: Fulltime

Data Platform Engineering Lead

Must Have Technical/Functional Skills

• Data Bricks
• EBT
• Airflow
• Asset Management exp

Roles & Responsibilities

We are seeking a highly skilled EDO 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.

This role is responsible for establishing and managing a scalable, secure, and highly available data platform that supports analytics, reporting, regulatory compliance, portfolio management, risk management, and investment operations.

Key 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.
• Infrastructure as a Code (IaC).
• Build reusable Terraform modules.
• Automate environment provisioning.
• Implement infrastructure standardization and governance.
• Maintain infrastructure version control.
• Ensure compliance through Infrastructure-as-Code practices.
• Design and implement CI/CD pipelines.
• Automate deployment and release management processes.
• Enable Infrastructure-as-Code and GitOps methodologies.
• Improve deployment velocity and reliability.
• Support engineering teams with self-service platform capabilities.
• GitHub Actions, GitLab CI/CD, Jenkins, Azure DevOps, Terraform, Docker, Kubernetes.
• Support API integrations and operational workflows.
• Establish Site Reliability Engineering (SRE) practices.
• Define platform SLAs, SLOs, and operational metrics.
• Lead platform monitoring, observability, and incident management.
• Drive root cause analysis and preventive actions.