Senior Data Engineer — APIs & Scalable Data Pipelines

DoubleVerify Inc.; New York (NY); Hybrid; USD 89,000 - 178,000; Full time

Job summary

DoubleVerify Inc. is seeking a Senior Data Engineer I to build data and integration capabilities at DV Scibids.

You will explore partner APIs, implement reliable data flows, and expose internal endpoints for DV teams, handling large-scale adtech datasets with modern engineering practices. You will collaborate with Product, Data Science, Analytics, and other Engineering teams to translate platform constraints into robust internal abstractions, ensuring observability, reliability, and performance

Qualifications

• 3+ years in data engineering or backend engineering.
• Strong Python and SQL skills.
• Experience integrating with external APIs and building production services.
• Familiarity with cloud environments, Git, CI/CD, and Docker.

Responsibilities

• Explore, evaluate, and integrate external partner APIs to support DV Scibids product expansion.
• Design, build, and maintain backend services and endpoints used by DV teams.
• Build robust data pipelines that ingest, transform, and reconcile data from partner platforms and internal systems.
• Work with large datasets from adtech auctions and ensure reliability at scale.
• Collaborate with Data Science, Analytics, Product, and other Engineering teams to align business needs with platform capabilities.
• Operate production systems, diagnose issues, and implement durable fixes.
• Continuously release features using automation and IaC tooling.

Skills

Python

SQL

Data engineering

APIs

Cloud environments

Git

CI/CD

Docker

Container orchestration

Tools

Docker

Kubernetes

REST APIs

Job description

DoubleVerify Inc. is seeking a Senior Data Engineer I to build data and integration capabilities at DV Scibids.

You will explore partner APIs, implement reliable data flows, and expose internal endpoints for DV teams, handling large-scale adtech datasets with modern engineering practices. You will collaborate with Product, Data Science, Analytics, and other Engineering teams to translate platform constraints into robust internal abstractions, ensuring observability, reliability, and performance