# Senior Data Engineer (Databricks) at LIVEFRONT

- Company: LIVEFRONT
- What the company does: Livefront develops and creates remarkable mobile apps. The team builds stunning mobile applications for people in motion and works on a regular basis. Backed by Rallyday Partners.
- Company website: https://livefront.com
- Type: Startups
- Level: Senior
- Location: Remote (USA)
- Work setup: Remote
- Pay: $150K to $180K base salary per year (USD)
- Posted: 2026-09-03
- Apply by: 2026-10-18
- Apply: https://job-boards.greenhouse.io/livefront/jobs/4395671009
- Page: https://www.1752.vc/careers/jobs/livefront-senior-data-engineer-databricks/

## About the role

We're looking for an outstanding Senior Databricks Data Engineer to join our growing data practice — someone who builds the data and AI foundations that digital products and intelligent experiences run on. You are a Databricks-focused Data Engineer who understands that great data platforms are only as valuable as the products, AI workflows, and experiences they enable. You bring deep, production-grade expertise across the Databricks platform and know how to connect platform capabilities to real business outcomes.

## What they're looking for

- 7-10 years of data engineering experience with at least 5 years in production Databricks environments, preferably in a consulting or client delivery context
- Solid working knowledge of AWS and Azure cloud services relevant to Databricks deployments — storage, networking, IAM, and compute — with GCP familiarity a plus
- Proven experience designing Lakehouse architectures — medallion patterns, Delta Lake table design, partitioning, Z-ordering, and query optimization — at production scale
- Hands-on experience with data pipeline testing, observability, and CI/CD for data — including unit testing, data quality frameworks, and version-controlled deployments via Git and Declarative Automation Bundles
- Strong proficiency in SQL and Python, with the ability to write clean, performant, and maintainable code
- Understanding of data modeling, schema design, and query optimization

Tags: Engineering, Data, & AI