Cloud Data Platform Lead — Modernization & Architecture

Guidehouse; San Antonio (TX); On-site; USD 92,000 - 153,000; Full time

Benefits offered by this job

Medical Insurance

401(k) Plan

Paid Holidays

Tuition Reimbursement

Employee Assistance Program

Job summary

Guidehouse is seeking a Data Engineer Lead to spearhead the design, development, and modernization of enterprise data platforms and analytics ecosystems. The role requires guiding cloud-native data solutions, setting standards, and mentoring engineers to deliver scalable, secure data workloads.

You will collaborate with architects, data scientists, and stakeholders to define roadmaps, optimize data models, and ensure data quality, observability, and security across hybrid environments.

Qualifications

• Seven or more years of experience in data engineering or related fields.
• Experience leading technical teams and complex data initiatives.
• Experience with modern data platforms and cloud-native data solutions.
• Experience with CI/CD and DevSecOps practices.

Responsibilities

• Lead design, development, and deployment of modern data platforms and analytics solutions.
• Define architecture, standards, and best practices for data integration, storage, and governance.
• Architect scalable ETL/ELT workflows, data lakes, and data warehouses.
• Provide technical leadership and mentorship to data engineers.

Skills

Data engineering leadership

Cloud architectures

Team leadership

CI/CD practices

Agile development

Communication

Problem solving

Education

Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, Data Science, or related field

Tools

Python

SQL

Spark/PySpark

Databricks

Snowflake

AWS

Azure

Kubernetes

Docker

Terraform

Job description

Guidehouse is seeking a Data Engineer Lead to spearhead the design, development, and modernization of enterprise data platforms and analytics ecosystems. The role requires guiding cloud-native data solutions, setting standards, and mentoring engineers to deliver scalable, secure data workloads.

You will collaborate with architects, data scientists, and stakeholders to define roadmaps, optimize data models, and ensure data quality, observability, and security across hybrid environments.