Data Engineer

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.

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.

Preferred Qualifications:

• 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.

Our Current Technology Landscape:

• ETL & Pipelines: Python, SQL


• Data Platform: Databricks (notebooks, jobs, cluster management)


• Analytics & BI: Tableau, Hex.tech, Alteryx, additional BI tooling


• Additional Tools: GitHub, Jira, Monday.com

Perks:

• 9/80 and 4.5/40 schedule options


• Hybrid work schedule


• Full health benefits


• 401(k) with 4% automatic contribution