Lead Data Analytics Engineer - Lakehouse & Spark

The University of Texas at Arlington Portal; Virginia (MN); On-site; USD 120,000 - 170,000; Full time

Job summary

The University of Texas at Arlington is seeking a Business Analytics Analyst Lead to design, develop, and optimize complex data pipelines and multi-dimensional data models within a lakehouse environment, utilizing Apache Spark or PySpark for scalable data processing. This role ensures seamless integration into enterprise architectures and drives improvements across the data landscape.

You will guide data teams, promote innovative data practices, and collaborate with senior leadership to deliver

Qualifications

• Bachelor’s degree or higher in Computer Science, Data Science, or a related discipline.
• Ten or more years of experience in data-related fields.
• Proven expertise in developing data architectures, models, and pipelines.
• Experience with Databricks and at least two of Python, SQL, Apache Spark, SAS, or R.

Responsibilities

• Leads design, development, and optimization of data pipelines in lakehouse using Spark or PySpark.
• Enhances system performance and scalability across lakehouse architectures.
• Designs multi-dimensional data models and integrations in lakehouse.
• Guides data teams in developing BI solutions and data governance.
• Identifies process improvements and presents strategic recommendations.
• Promotes best practices for scalable, cost-effective data solutions.
• Performs other duties as assigned.

Skills

Databricks

Python

SQL

Apache Spark

SAS

R

Education

Bachelor’s degree

Master’s degree

Tools

Databricks

Job description

The University of Texas at Arlington is seeking a Business Analytics Analyst Lead to design, develop, and optimize complex data pipelines and multi-dimensional data models within a lakehouse environment, utilizing Apache Spark or PySpark for scalable data processing. This role ensures seamless integration into enterprise architectures and drives improvements across the data landscape.

You will guide data teams, promote innovative data practices, and collaborate with senior leadership to deliver