Lead Data Engineer

Globenet Consulting Corp•BELLEVUE, WA

3d•$45 - $55•Onsite

About The Position

The AES Group Inc. is seeking an experienced Lead Data Engineer to support one of our enterprise clients. This role will lead the design, development, and optimization of scalable cloud data platforms while establishing engineering standards and mentoring team members. The ideal candidate will have recent hands-on experience with Azure Databricks, Python, PySpark, SQL, ETL/ELT development, and modern data warehouse architecture.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Information Technology, or a related field, or equivalent experience.
At least 3 years of hands-on Azure Databricks experience.
Strong knowledge of current Azure Databricks features and capabilities.
At least 5 years of data warehouse analysis, architecture, and design experience.
Strong knowledge of dimensional modeling, operational data stores, and enterprise integration.
At least 5 years of ETL/ELT development using Python, PySpark, and SQL.
Experience with Terraform, Git, CI/CD pipelines, and Azure DevOps.
Demonstrated experience leading and mentoring data engineering teams.
Strong communication, problem-solving, and stakeholder-management skills.

Nice To Haves

Databricks Data Engineer Associate or Professional certification.
Experience with Unity Catalog, Azure RBAC, managed identities, and data governance.
Familiarity with Power BI and MicroStrategy architecture.
Experience in regulated, quality-focused, or compliance-driven environments.

Responsibilities

Design and optimize scalable data pipelines and ETL/ELT workflows using Azure Databricks, PySpark, SQL, and Delta Lake.
Provide technical leadership, mentoring, and guidance to data engineers.
Improve CI/CD pipelines using Azure DevOps, Git, Terraform, and automated deployment frameworks.
Establish standards for development, testing, code quality, and release management.
Ensure data accuracy through integration, transformation, validation, and cleansing processes.
Use Python and PySpark for automation, data processing, and performance optimization.
Support migrations from legacy environments to modern cloud data platforms.
Translate business and technical requirements into scalable data solutions.
Apply governance and security practices using Unity Catalog, Azure RBAC, managed identities, and access controls.
Support Power BI reporting environments and provide exposure to MicroStrategy.
Participate in on-call support and resolve production issues when required.