Software Development Engineer 3

About the role

Immigration / Work Authorization Notice: Applicants must be currently authorized to work in the United States. iSpot is not able to sponsor or take over sponsorship of an employment visa for this position at this time.

iSpot competes for the best talent. Our compensation packages consist of salary and equity in one of Seattle’s hottest start-ups, as well as other standard benefits. Most importantly, we provide a really interesting working experience, and the chance to contribute to the success of something great.

What You’ll Be Part Of:

Ad Optimization builds the pipelines and integrations that deliver iSpot's TV and streaming measurement (impressions, conversions, and attribution) to partners such as DSPs, CTV platforms, and ad servers, so advertisers can optimize campaigns in flight. As an SDE III data engineer on the team, you will build and own the Spark and Snowflake pipelines behind these partner optimization feeds, from design through production operation.

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, including 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 ambiguous requirements to production.

- Own releases and deployments to team standards, including staged rollouts and rollback.

- Participate in the team's on-call rotation. You will respond to alerts and incidents, lead root-cause analysis, and keep 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 what they produce.

Qualifications and Education 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 transformations, performance and cost tuning (warehouse sizing, clustering, query profiling), and tasks and streams or dynamic tables for scheduled and incremental processing.

- 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.