Data Platform Engineering Lead

ClifyX; Irvine (CA); On-site; USD 150,000 - 180,000; Full time

Job summary

ClifyX is seeking a Data Platform Engineering Lead in Irvine to architect, build, and manage enterprise-scale cloud-native data platforms for Asset Management functions. You will lead platform engineering, infrastructure automation, DevOps enablement, and platform reliability across the Enterprise Data Office.

The ideal candidate brings deep Databricks, dbt, AWS, Terraform, Python, and SRE practices, with experience supporting investment management.

Qualifications

• Experience with enterprise-scale Databricks and Airflow for data platforms.
• Strong AWS Cloud, Terraform, and Python skills for platform engineering.
• Asset management domain knowledge is highly desirable.
• Proven ability to design scalable, secure data architectures.

Responsibilities

• Lead design, implementation, and management of enterprise data platforms.
• Define platform engineering strategy aligned with enterprise standards.
• Establish reusable frameworks and best practices.
• Drive cloud-native modernization across data and analytics.
• Own platform lifecycle, scalability, and reliability.
• Lead Databricks architecture and administration.
• Design Lakehouse using Delta Lake.
• Implement IaC, CI/CD, and GitOps practices.
• Support self-service platform capabilities and governance.

Skills

Databricks

Airflow

AWS Cloud

Terraform

Python

DevOps

Platform Engineering

Data Operations

dbt

Job description

Job Title: Data Platform Engineering Lead

Location: Irvine, CA Onsite

Must Have Technical/Functional Skills

Data Bricks , EBT ,Airflow , Asset Management exp

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,Lamda .Glue ,Cloudwatch
• Infrastructure as a Code (IaC)
• Implement infrastructure standardization and governance.
• 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.
• 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