Data Engineer - Lakehouse & Power BI

DataJobs; Spring (TX); On-site; USD 85,000 - 110,000; Full time

Benefits offered by this job

Medical Insurance

401K matching

Paid Time Off

In-person work

Job summary

TWFG Insurance in Spring, TX is seeking a Data Engineer to design and maintain scalable data pipelines and lakehouse architectures powering analytics and reporting for insurance operations.

You will build and optimize ELT/ETL pipelines, create semantic models, and integrate data from multiple systems, including APIs. Strong SQL, Python/PySpark, and cloud experience are essential, with a focus on governance and CI/CD.

Qualifications

• Bachelor's degree or equivalent professional experience in a related field.
• 3+ years of experience in Data Engineering, Analytics Engineering, or Data Warehousing.
• Experience designing and supporting enterprise-scale data pipelines.
• Strong SQL development skills.
• Experience with Python and/or PySpark.
• Experience with cloud data platforms: Azure, AWS or GCP.

Responsibilities

• Design and maintain scalable ELT/ETL pipelines using Microsoft Fabric and PySpark notebooks.
• Develop lakehouse layers within a Medallion architecture.
• Create dimensional models and semantic datasets for reporting and analytics.
• Integrate data from policy, carrier, vendor platforms, and APIs.
• Implement data quality controls, validation, and monitoring processes.
• Develop and maintain Fabric Lakehouses, Mirrored Databases, Dataflows, Notebooks, and Pipelines.
• Support Power BI Embedded analytics and enterprise reporting.

Skills

SQL

Python

PySpark

Microsoft Fabric

Power BI

Azure/AWS/GCP

Data Modeling

Education

Bachelor's degree

Tools

Microsoft Purview

REST APIs

Azure Data Platform

Job description

TWFG Insurance in Spring, TX is seeking a Data Engineer to design and maintain scalable data pipelines and lakehouse architectures powering analytics and reporting for insurance operations.

You will build and optimize ELT/ETL pipelines, create semantic models, and integrate data from multiple systems, including APIs. Strong SQL, Python/PySpark, and cloud experience are essential, with a focus on governance and CI/CD.