Junior Data Engineer

About the company:

Scibids DoubleVerify is a global leader in AI-powered digital campaign activation. Scibids empowers global brands to drive specific KPIs and tangible outcomes more effectively while improving operational efficiency and reducing manual lift. Scibids technology does not rely on digital identifiers such as cookies and can be activated across leading Demand-Side Platforms such as The Trade Desk or DV360, and other buy-side platforms (Meta, Google Ads, Tiktok). To learn more visit https://doubleverify.com/scibids-ai/

DoubleVerify acquired Scibids in 2023,  providing an End-to-end, comprehensive measurement and granular optimization solution. DoubleVerify is the recognized market innovator with the technology and tools that accurately authenticate the quality of digital media and drive ad performance for the world's largest brands. DV provides media transparency and accountability to deliver the highest level of impression quality for maximum advertising performance.  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 ecosystem that help build a better industry. Learn more at doubleverify.com

About the role:

Do you like to build efficient data platforms, dealing with multiple constraints (volume, throttling, canonization, freshness, lineage) in a pragmatic way ? 

The mission of DoubleVerify Scibids is to provide media buyers with fully automated buying strategies for their campaigns, leading to unparalleled  performances for a minimum of human work. 

The Data Engineering team is at the core of the Scibids products, and is responsible for communication between Scibids and its partners. We rely on a combination of open source and in-house solutions to provide accurate and reliable data. We ingest diverse and sometimes massive data streams. The team also manages outbound communications with partners: we leverage partner apis, cross-referenced with a set of business rules, to upload models generated by the Data Science teams.

For example, in Q1 2025 we just finished integrating new data from Amazon and Google Ads (file ingestion, schema mapping, and API integration to push models and get configuration data).

This role has a specific emphasis on tooling and automation, to support many initiatives, ranging from monitoring to CI/CD to auditing. As the rest of the Data Engineering team you’ll be at the crossroads of many teams and will sometimes be coordinating their work.

 

As Data Engineer,  you’ll be involved in a wide range of activities, including:

 

• Core Data engineering tasks 

Creation of ETL jobs to make our partners' data available to other teams. There are several sources of data, for example data from api or files in csv, avro or parquet format with several million rows.

• Technical Project Coordination:

Support the implementation of small-scale migrations, updates, and infrastructure changes. Work closely with senior engineers to ensure smooth project execution.

Partner with infrastructure, data, and security teams to identify bottlenecks and build tailored automation solutions that enhance team efficiency and reduce manual work

• Compliance & Security:

Contribute to automated compliance and security initiatives, such as monitoring audit logs and supporting penetration testing activities.

What we are looking for

Experience

0-2 years of experience in a technical or engineering support role, including personal projects or internships.

Technical Skills

Scripting: proficiency in Python (preferred)

General SQL knowledge (we mostly use Mysql and BigQuery)

Cloud Platforms: Familiarity with one of AWS, GCP, or Azure (we use Google)

API Understanding: Basic understanding of REST APIs and their use in data integration.

Workflow Orchestration: basic knowledge of (or ability to grasp) tools like Prefect, Airflow, GitHub Actions.

 

Soft Skills

Problem-Solving: A proactive attitude and the ability to investigate and resolve technical issues.

Communication: Clear and concise written and verbal communication skills.

Organization: Ability to manage multiple tasks and prioritize effectively.

Learning Agility: A genuine desire to learn new technologies and adapt to changing priorities.

 

Reporting to: Manager, Data Engineering

 

Scibids offers a dynamic, inclusive environment where innovation and teamwork are celebrated. If you are looking to make a significant impact in the digital marketing sphere and lead a talented team towards groundbreaking achievements, we would love to hear from you.

#Hybrid