Senior Databricks Data Platform Engineer

nOps; Northern (KY); Hybrid; USD 140,000 - 200,000; Full time

Job summary

nOps is seeking a Senior Data Platform Engineer to own the health, performance, and cost-efficiency of our data platform. You’ll build end-to-end data pipelines from ingestion to customer-facing dashboards and work across engineering, finance, and product to drive data accuracy and reliability.

Bring 5+ years in a hybrid data engineering/data science role with deep Databricks expertise, strong SQL and Python skills, and familiarity with AWS data infrastructure.

Qualifications

• 5+ years in hybrid data engineering / data science
• Deep Databricks expertise (Lakehouse, pipelines, optimization)
• Strong SQL and Python proficiency
• Working knowledge of AWS data infrastructure
• Ability to trace data issues across the full stack
• Curiosity with a builder mindset and ownership to fix inefficiencies
• Strong communication skills for non-technical stakeholders
• Excitement for a fast-moving Series A environment with end-to-end ownership

Responsibilities

• Own daily health and performance of Databricks Lakehouse, jobs, pipelines, security, and workspace cleanup
• Build and maintain data pipelines in SQL and Python transforming data into consumable formats
• Optimize legacy jobs and workflows for performance and cost efficiency
• Own security administration in Databricks (users, groups, RBAC)
• Trace data flows end-to-end from Databricks to front-end to customer view
• Partner with engineering, customer success, and product to ensure data accuracy and integrity
• Manage the AWS infrastructure powering the data environment

Skills

Databricks

SQL

Python

AWS

Tools

Databricks Lakehouse

Neon

Lakebase

Supabase

Aurora Postgres

Job description

nOps is seeking a Senior Data Platform Engineer to own the health, performance, and cost-efficiency of our data platform. You’ll build end-to-end data pipelines from ingestion to customer-facing dashboards and work across engineering, finance, and product to drive data accuracy and reliability.

Bring 5+ years in a hybrid data engineering/data science role with deep Databricks expertise, strong SQL and Python skills, and familiarity with AWS data infrastructure.