Avatar for nOps
nOps
Actively Hiring
Automated Cloud Optimization Platform
  • B2B
  • Growth Stage
    Expanding market presence

Senior Data Platform Engineer

Posted: 4 weeks ago• Recruiter recently active
Hires remotely in
Remote Work Policy

Remote only

Company Location
Visa Sponsorship

Not Available

Preferred Timezones
Pacific Time, Mountain Time, Central Time, Eastern Time
RelocationNot Allowed
Skills
Python
SQL
PostgreSQL
ETL
AWS
Pyspark
databricks
Delta Lake
Role-Based Access Control (RBAC)

About the job

About nOps

nOps is a Series A FinOps platform managing over $4B in cloud spend across AWS, Azure, and GCP. We help engineering and finance teams gain real-time cloud cost visibility and achieve autonomous optimization.

The Role

We're looking for a Senior Data Platform Engineer who blends data engineering and data science to help power the next stage of our growth. You'll own the health, performance, and cost-efficiency of our data platform while building the pipelines that drive our product forward. You'll be a key partner across the team — someone who loves digging into how data flows end-to-end, from raw ingestion through to what our customers see in the app, and who takes pride in getting to the root of things.

What You Will Do

  • Own the daily health and performance of our Databricks Lakehouse environment (jobs, pipelines, security, workspace cleanup)
  • Build and maintain data pipelines in SQL and Python that transform data into consumable formats
  • Optimize legacy jobs and workflows for performance and cost efficiency
  • Own security administration in Databricks (users, groups, role-based access control)
  • Trace data flows end-to-end across the stack — from Databricks through the front-end to what the customer sees
  • Partner closely with engineering, customer success, and product to ensure data accuracy and integrity across the platform
  • Manage the AWS infrastructure that powers our data environment

What You Will Bring

  • 5+ years of experience in a hybrid data engineering / data science role
  • Deep expertise with Databricks (Lakehouse, pipeline development, optimization)
  • Strong proficiency in SQL and Python
  • Working knowledge of AWS infrastructure as it relates to data platform operations
  • Comfort tracing data issues across the full stack
  • Curiosity and a builder mentality — someone who loves spotting inefficiencies and takes ownership of fixing them
  • Strong communication skills, especially explaining complex data topics to non-technical stakeholders
  • Excitement for a fast-moving Series A environment where you can own outcomes end-to-end

Nice to Have

  • 2+ years experience with Neon, Lakebase, Supabase, or Aurora Postgres
  • Experience with cost optimization at scale on Databricks
  • Familiarity with role-based access control (RBAC) and data governance
  • Background in FinOps, cloud cost management, or SaaS analytics platforms

Our Stack

  • Data: Databricks Lakehouse, Lakebase, PySpark, SQL, Python
  • Cloud: AWS
  • Front-End / Back-End: Next.js, Vercel
  • Data Layer: Postgres

About the company

nOps company logo

nOps

Actively Hiring
Automated Cloud Optimization Platform51-200 Employees
  • B2B
  • Growth Stage
    Expanding market presence

Employees joined from

Learn more about nOps image

Funding

AMOUNT RAISED
$39.5M
FUNDED OVER
5 rounds
Rounds
A
$30000000
Series A - Aug 2024+4

Founders

Sumit Gupta
Founder • 10 years
San Francisco
image
JT Giri
Founder
Silicon Valley
image
View the team image

Similar Jobs

Albeado company logo
Albeado
Breakthrough causal AI predictions, optimizations and interventions - in real time
Voicera.io company logo
Voicera.io
Believe what you hear. Trust what you see
Dreamers company logo
Dreamers
Specializing in building technological solutions for complex problems
Ground Signal company logo
Ground Signal
Sales optimization for the Alcohol industry
Wynd Labs company logo
Wynd Labs
Making AI Data Accessible. Building a suite of products powered by Grass
Deepgram company logo
Deepgram
AI speech API for transcription with human-level understanding