Software Development Engineer 3

Description

The company is a Seattle-area start-up that measures TV and streaming advertising, covering impressions, conversions and attribution.

The Ad Optimization team builds the pipelines and integrations that send this measurement to partners such as DSPs, CTV platforms and ad servers, so advertisers can adjust live campaigns.

As an SDE III data engineer, you will build and own the Spark and Snowflake pipelines behind these partner optimization feeds, from design through production.

Applicants must be currently authorized to work in the United States. The company cannot sponsor or take over sponsorship of an employment visa for this position at this time.

Responsibilities

• Build, tune and maintain large-scale batch Spark pipelines that turn measurement data into partner-ready optimization feeds.
• Build and optimize Snowflake processing, including SQL transformations, scheduled and incremental pipelines, and data modeling.
• Tune pipeline performance and cost across Spark and Snowflake.
• Design data models, table layouts and partitioning across S3, lakehouse tables and Snowflake.
• Build partner data feeds, covering file and API deliveries, identity matching, privacy-sensitive data handling and delivery SLAs.
• Build data-quality checks, reconciliation, telemetry and alerting, and handle late-arriving data and backfills.
• Write and review technical designs and test plans, and lead small-to-medium projects from unclear requirements to production.
• Own releases and deployments to team standards, including staged rollouts and rollback.
• Join the team's on-call rotation, responding to alerts and incidents, leading root-cause analysis and keeping runbooks current.
• Mentor other engineers through code review, pairing and design feedback.
• Use AI-assisted tools for design, development, testing and incident work, and verify their output.

Requirements

• 5+ years of professional software or data engineering experience.
• 3+ years building, optimizing and operating production Apache Spark pipelines in Java or Scala and in Python/PySpark.
• 2+ years of production Snowflake experience, including complex SQL, performance and cost tuning (warehouse sizing, clustering, query profiling), and tasks, streams or dynamic tables for scheduled and incremental work.
• 2+ years running data workloads on AWS, including S3 and Spark on Kubernetes (EKS) or EMR.
• Production experience with Airflow or an equivalent workflow orchestrator.
• Advanced SQL and relational data modeling.
• Experience building external partner or client data feeds involving file and API deliveries, identity matching, privacy-sensitive data and delivery SLAs.
• Experience designing data-quality checks, reconciliation, telemetry and alerting for batch pipelines, including late-arriving data and backfills.
• Experience writing unit and integration tests for data pipelines.
• Production ownership across CI/CD, releases and rollback, incident response and root-cause analysis.
• Experience writing and reviewing technical designs and leading small-to-medium engineering projects through production delivery.
• Experience mentoring engineers through code review, pairing and design feedback.
• Experience using AI-assisted engineering tools responsibly, verifying output for security, correctness and maintainability.
• Preferred Skills:
• Experience with Snowflake external Iceberg tables and catalog integrations, secure data sharing or Snowpark (Python).
• Experience with Apache Iceberg and MySQL.
• Experience running Spark on Amazon EKS and Airflow on Amazon MWAA.
• Experience in ad tech or advertising measurement, such as attribution, conversions, audience and impression data, identity matching or partner optimization feeds.

Conditions

Target cash compensation is $117,688 - $148,289 USD per year.

Cash compensation includes base salary, variable commission for eligible roles, and annual bonus targets for eligible roles. Pay is set by factors such as skills, experience and qualifications.

Non-exempt roles are also eligible for pre-approved overtime pay.

Hybrid work: employees working near the Bellevue, WA or New York, NY offices come in 1-3 days a week. Those located further away in roles not based in an office work fully remote.

Your recruiter can explain the details of the hybrid and flexible workplace policy.

The company welcomes applicants who do not meet every requirement.

California residents can read the California Consumer Privacy Act notice on the company's site.

Benefits

• Full-time employees are eligible for stock options under the company's equity plan.
• Other standard benefits are offered.
• The total rewards package is described on the company's site.