Sr. Analytics Data Platform Engineer

Who We Are DV is the leader in digital performance solutions, helping our advertiser and agency partners Verify the quality of their digital campaigns, Optimise to improve performance and Prove that they’re achieving their business outcomes, through unbiased 3rd party data and analytics. DV’s mission is to be the definitive source of transparency and data-driven insights into the quality and effectiveness of digital advertising for the world’s largest brands, agencies, publishers, and digital ad platforms.  Since 2008, DV has helped hundreds of Fortune 500 companies gain the most from their media spend by delivering best-in-class solutions across the digital advertising ecosystem, helping to build a better industry. Learn more at www.doubleverify.com . About the Role Role Overview You will join the Data & Analytics Platform (DAP) team within the Pinnacle engineering organization. The DAP team owns and operates two data consolidation platforms — Quantum (contract-driven, next-gen) and Analytics 2.0 (SQL-driven, legacy) — that ingest, transform, and serve billions of records daily from social platforms, measurement systems, and third-party partners. The data powers Looker dashboards, customer-facing reports, and downstream APIs used across DoubleVerify's product suite. What You'll Do Platform Abstraction & Design: Design and maintain the YAML-based "Contract" system that allows users to define data entities, transformations, and SLOs without writing low-level orchestration code. Infrastructure as Code (IaC): Develop the translation engine that converts user contracts into automated dbt models, Airflow DAGs, and Snowflake objects. API Development: Transition the platform from static configuration files to a dynamic, API-first architecture, enabling programmatic creation of data artifacts. Self-Service Enablement: Build tooling and guardrails that allow business units to deploy their own data solutions while maintaining global standards for governance and security. Performance & Scale: Optimize the "translation" layer to ensure that generated jobs are efficient, cost-effective, and leverage the full power of the Snowflake/dbt stack. Developer Experience (DevEx): Act as the "Product Manager" for your platform, gathering feedback from internal users to simplify the data development lifecycle. Design and build data pipelines that process billions of records a day across consolidation, semantic, and externalization layers using the DV Internal Data Platform — a self-service, contract-driven architecture where pipelines are defined via YAML contracts and automatically deployed to Snowflake, Airflow, and Looker. Develop and extend the Contract Interpreter — a Python library (Pydantic, Jinja2) that reads contract driven platform based YAML and generates dbt models, Airflow DAGs, and environment configurations for each deployment environment (dev, stg, prod). Lead new initiatives and integrations with the world's largest…