Sr. Analytics Data Platform Engineer

DoubleVerify Inc.; New York (NY); On-site; USD 107,000 - 212,000; Full time

Job summary

DoubleVerify Inc. is seeking a Senior Data Engineer to join the Data & Analytics Platform (DAP) team. You will help own and evolve two data platforms, ingesting billions of records daily and powering Looker dashboards and APIs across DoubleVerify’s product suite.

The role emphasizes SQL proficiency, Python development, dbt and Snowflake expertise, plus building scalable data pipelines, AI-assisted tooling, and governance-friendly solutions for global teams.

Qualifications

• Bachelor's degree in Computer Science, Data Engineering, or related field.
• 5+ years of experience in Data Engineering or related role.
• Strong SQL skills with advanced querying and transformations at scale.
• Proficiency in Python for libraries, data processing, and automation (Pydantic/Jinja2 a plus).
• Deep experience with Snowflake, dbt, and orchestration tools like Airflow.
• Experience with cloud platforms (GCP) and CI/CD pipelines.
• Familiarity with Looker/LookML for semantic modeling and dashboards.

Responsibilities

• Design and maintain the YAML-based Contract system to define data entities, transformations, and SLOs.
• Develop translation engine to convert contracts into dbt models, Airflow DAGs, and Snowflake objects.
• Move platform to API-first architecture enabling programmatic data artifact creation.
• Build tooling and guardrails for self-service data solutions while enforcing governance.
• Optimize the translation layer for performance, cost, and scalability on Snowflake/dbt.
• Act as the Product Manager for the platform, gathering user feedback to simplify workflows.
• Develop data pipelines processing billions of records daily across consolidation and analytics layers.
• Extend the Contract Interpreter (Python) to generate deployment configurations for dev/stg/prod.
• Lead integrations with major social platforms to measure ad performance end-to-end.
• Build Looker semantic models, explores, and views to deliver customer-ready analytics.
• Implement observability with monitoring and data quality checks to ensure freshness.
• Leverage AI agents and tooling to accelerate development and encode institutional knowledge.
• Design schema evolution and data migration strategies including versioning and backfills.
• Collaborate with partner engineers on API development and data integration.
• Mentor a team of software engineers.

Skills

SQL

Python

Snowflake

dbt

Airflow

Looker/LookML

Kubernetes

CI/CD

AI tools

Data modeling

Education

Bachelor's degree in Computer Science/Data Engineering

Tools

dbt

Airflow

Snowflake

Looker

Kubernetes

GCP

Job description

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.

DV provides the industry’s leading Media Effectiveness Platform. Utilizing trusted measurement data and dynamic AI optimization, DV maximizes campaign effectiveness and drives tangible business outcomes for advertisers wherever they run their digital media. DV powers performance for the world's largest brands, platforms and publishers. We believe this is important work. Why? Because when an ad-supported ecosystem hums, it preserves a free internet for us all. We're looking for the best and the brightest talent, those who stand for one another and meet challenges with a spirit of ingenuity and invention.

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 social platforms (YouTube, TikTok, Meta, Snapchat, Reddit, Netflix, etc.) to measure ad performance end-to-end.


• Build and maintain the semantic layer - design LookML models, explores, and views that translate consolidated data into customer-ready analytics through Looker.


• Implement and maintain observability - build monitoring, alerting, watermarking, and data consistency checks to ensure pipeline reliability and data freshness at scale.


• Leverage AI agents and tooling - contribute to and use the team's AI agent workspace (meta-repo with AGENTS.md context files, skills, and MCP integrations) to accelerate development, automate workflows, and encode institutional knowledge for AI-assisted engineering.


• Design schema evolution and data migration strategies - manage schema versioning, backward compatibility, incremental vs. full-refresh deployments, and large-scale data backfills.


• Work in multi-functional agile teams with end-to-end responsibility for product development and delivery - from contract definition to customer-facing data.


• Collaborate directly with engineers from partner platforms on API development and data integration specifications.


• Train and mentor a team of software engineers.

Who You Are

Required Experience & Qualifications

• Bachelor's degree or foreign equivalent in Computer Science, Data Engineering, or a related field.


• 5+ years of experience in a Data Engineering or related role.


• Strong SQL skills — advanced querying, performance tuning, window functions, and complex transformations at scale.


• Proficiency in Python — building libraries, data processing scripts, and automation tooling (experience with Pydantic, Jinja2, or similar templating frameworks is a plus).


• Deep experience with Snowflake — schema design, Snowpipe, streams, tasks, materialized views, clustering, and query optimization.


• Experience with dbt (data build tool) — building and maintaining models, macros, custom materializations, and incremental strategies.


• Experience with orchestration tools — Airflow / Cloud Composer, DAG design, scheduling, and monitoring.


• Experience with cloud platforms — GCP (GCS, BigQuery, Cloud Composer, Kubernetes) or equivalent.


• Strong understanding of data warehousing concepts — dimensional modeling, star/snowflake schemas, slowly changing dimensions, fact/aggregate table design, and data consistency patterns.


• Experience with CI/CD pipelines — GitLab CI, Flyway migrations, or similar deployment automation.


• Experience with AI-assisted development tools — Claude Code, Cursor, GitHub Copilot, or similar AI coding assistants.


• Experience building or contributing to AI agent context files (AGENTS.md), skills, or meta-repo patterns is a strong plus.

Preferred Experience & Qualifications

• Experience building or working with contract-driven / configuration-driven data platforms where pipelines are generated from declarative specifications (YAML, JSON schemas).


• Experience with Looker / LookML — building semantic models, exploring, aggregating awareness, and dashboard development.


• Experience with Kafka — schema registries, topic management, and streaming data integration.


• Experience with data quality and observability frameworks — automated testing, watermarking, data integrity validation, and SLA monitoring.


• Experience with Terraform or infrastructure-as-code for managing cloud resources.


• Familiarity with data mesh principles — federated data ownership, data products, and self-service platform design.

The successful candidate’s starting salary will be determined based on a number of non-discriminating factors, including qualifications for the role, level, skills, experience, location, and balancing internal equity relative to peers at DV. The estimated salary range for this role based on the qualifications set forth in the job description is between $107,000- $212,000. This role will also be eligible for bonus/commission (as applicable), equity, and benefits. The range above is for the expectations as laid out in the job description; however, we are often open to a wide variety of profiles, and recognize that the person we hire may be more or less experienced than this job description as posted.