Data Engineer

KEA•Rockwall, TX

2d•Hybrid

About The Position

We have an immediate opportunity for an Entry to Mid-level Data Engineer to join our technology team. In this role, you will collaborate with other engineers, our internal product committee, and end-users to deliver high quality data solutions for large-scale property tax management. This position, and KE Andrews as a company, is geared towards individuals with a long-term outlook that want to turn a role into a career, not just work a job.

Nice To Haves

0–5 years of experience in data engineering or a related role.
Familiarity or hands-on experience with technologies such as: ETL & Transformation: Python, SQL Data Platform: Databricks, Snowflake, Synapse/Fabric Analytics & BI: Tableau, and other BI tools
Strong problem-solving skills and attention to detail.
Effective communicator who enjoys working in a collaborative team environment.
A passion for continuous learning and growing as a data engineer.

Responsibilities

Design, build, and maintain Python-based ETL pipelines to ingest, transform, and load data from a variety of sources.
Write and optimize SQL-based ETL workflows and data transformations to support downstream analytics and reporting.
Develop and manage data workflows within Databricks, including notebooks, jobs, and cluster configurations.
Support and maintain data models and datasets consumed by Tableau, Alteryx, Hex and other BI tools.
Monitor pipeline performance, troubleshoot data quality issues, and implement fixes as needed.
Collaborate with analysts and business stakeholders to understand data needs and translate them into engineering solutions.
Participate in requirements discussions and design sessions with senior engineers and product stakeholders.
Occasionally serve as support lead, rotating through the team to handle production-related data requests.
Document pipelines, data models, and processes to support team knowledge sharing.
Collaborate with teammates during standups, demos, pull request reviews, sprint planning, and retrospectives.