Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from The Trade Desk
The Trade Desk is a global technology company and the world’s leading independent platform for digital advertising, with nearly 4,000 employees across more than 30 offices. Our technology helps advertisers reach the right audiences across the open internet — from streaming TV and podcasts to mobile apps, news, and more.
Advertising powers the content people love. By making it more transparent, effective, and responsible, we help support trusted journalism, quality entertainment, and creators worldwide. The world’s brands and agencies rely on us to reach their customers and grow their businesses responsibly.
The scale of our platform brings unique technical challenges — from processing massive datasets in real time to building systems that operate reliably on a global scale. When you work here, your impact is worldwide. We welcome diverse perspectives, encourage curiosity, and build teams that learn from one another. If you’re driven to solve meaningful challenges, we’d love to meet you.
ABOUT THE ROLE
This role sits within the Technology Operations group in Engineering at The Trade Desk and focuses on building reliable, scalable, and well‑governed enterprise data solutions. As a Senior Software Engineer – Data Engineer, you will be an end‑to‑end owner for complex data pipelines, models, and integrations that power analytics, reporting, and internal products.
This is a hands-on senior role with growing technical leadership expectations. You will work independently on ambiguous problems, influence design decisions, and mentor others, while still operating within an established architecture and technical direction.
WHAT YOU WILL DO:
- Own complex data pipelines end to end. Design, build, and operate scalable batch and near‑real‑time ETL/ELT pipelines using Snowflake, Databricks, Spark, and cloud storage.
- Drive data modeling and warehouse design. Define and implement dimensional models, data marts, and curated datasets that balance performance, usability, and governance.
- Raise data quality and reliability. Implement robust data quality checks, validations, monitoring, and alerting to ensure data accuracy, freshness, and trust.
- Collaborate deeply with stakeholders. Partner with product managers, BI teams, data scientists, and internal business teams to translate business needs into well‑designed data solutions.
- Lead design without owning architecture. Proactively propose technical improvements, review designs, and influence standards while aligning with broader platform and architectural direction.
- Mentor and raise the bar. Provide technical guidance through code reviews, pairing, and documentation; help mid‑level and junior engineers grow in ownership and quality.
- Operational excellence. Improve performance, scalability, cost efficiency, and observability of data systems; participate in on‑call and incident response as needed.
WHO YOU ARE:
- Bachelor's degree in computer science, information security, or a related field, or equivalent work experience. Masters degree preferred and 6-8+ years of professional experience in software or data engineering
- Strong expertise in SQL and data modeling for analytics and reporting
- Hands‑on experience with Snowflake and/or Databricks modern data warehouse concepts
- Experience building and operating ETL/ELT pipelines using tools such as Airflow, Dagster, Glue, or similar
- Proficiency in Python, Scala, Java, or similar languages
- Familiarity with Spark–based data processing
- Solid understanding of version control (Git) and CI/CD practices
- Experience with data quality, observability, and operational support
- Strong senior‑level engineer. You can independently deliver complex data solutions and make sound technical tradeoffs, even when requirements are incomplete.
- Pragmatic and detail‑oriented. You care deeply about correctness, reliability, and maintainability—not just shipping code.
- Collaborative and influential. You communicate clearly, build trust across teams, and influence outcomes without requiring formal authority.
- Continuously learning. You stay current on data engineering patterns, tooling, and best practices and apply them thoughtfully
PREFERRED QUALIFICATIONS
- Experience working at petabyte‑scale or high‑growth data environments
- Familiarity with governance, security, and compliance (e.g., PII handling, access controls)
- Exposure to containerization (Docker, Kubernetes) or cloud infrastructure patterns
- Experience in AdTech or analytics‑heavy domains
- Comfort working with BI and reporting tools and understanding downstream consumption needs
Variety of technical opportunity is one of the best things about working at The Trade Desk as a software engineer which is why we do not expect you to know every technology we use when you start. What we care about is that you can learn quickly and find solutions to complex problems using the optimum tools for the job. What you know is less important than how well you learn and innovate. W
Source: The Trade Desk careers