Data Platform Engineering Lead

Ventures Unlimited Inc; Irvine (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

Ventures Unlimited Inc in Irvine, CA seeks an EDO Platform Engineering Lead to architect, build, and manage an enterprise-scale cloud-native data platform for Asset Management functions.

You will lead platform engineering, infrastructure automation, DevOps enablement, platform reliability, and security across the Enterprise Data Office, leveraging Databricks, AWS, Terraform, and Python to support analytics, reporting, regulatory compliance, and investment operations.

Qualifications

• Extensive experience architecting and operating enterprise data platforms for financial services.
• Deep expertise in Databricks, AWS, Terraform and Python across large-scale data workloads.
• Proven ability to lead platform engineering, DevOps enablement, and SRE practices.

Responsibilities

• Lead design, implementation and management of enterprise data platforms.
• Define platform engineering strategy aligned with enterprise 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.
• Design Lakehouse architecture leveraging Delta Lake.
• Manage Databricks Workflows, DLT, Unity Catalog, MLflow and streaming.
• Implement IaC, governance and CI/CD pipelines.
• Support self-service platform capabilities and API integrations.

Skills

Databricks

dbt

AWS Cloud

Terraform

Python

DevOps

Platform Engineering

Data Operations

Tools

Databricks Workflows

Delta Live Tables

Unity Catalog

MLflow

Structured Streaming

Cluster Policies

Security and Access Controls

S3

ECS

EKS

Lambda

Glue

CloudWatch

IaC

GitOps

CI/CD

Job description

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