Software Development Engineer 3

iSpot•Bellevue, WA

3h•$117,688 - $148,289•Hybrid

About The Position

As a Software Development Engineer 3 data engineer on iSpot’s Ad Optimization team, you will build and own the Spark and Snowflake pipelines behind partner optimization feeds, from design through production operation. The team builds pipelines and integrations that deliver iSpot’s TV and streaming measurement—including impressions, conversions, and attribution—to partners such as DSPs, CTV platforms, and ad servers so advertisers can optimize campaigns in flight. The role involves developing large-scale data pipelines and partner feeds, improving performance and cost, and ensuring reliable, privacy-conscious delivery. You will own releases and production operations, participate in on-call, lead technical work through production, and mentor engineers. The role also uses AI-assisted tools for engineering work, with verification of their output. The position is hybrid for employees local to or near the Bellevue, Washington, or New York, New York offices, with office attendance 1–3 days per week. Employees who are not office-based and live farther from those offices work fully remotely. Applicants must already be authorized to work in the United States; visa sponsorship or transfer is not available for this position.

Requirements

At least 5 years of professional software or data engineering experience.
At least 3 years building, optimizing, and operating production Apache Spark pipelines in Java or Scala and in Python/PySpark.
At least 2 years of production Snowflake experience, including complex SQL transformations, performance and cost tuning (warehouse sizing, clustering, and query profiling), and tasks and streams or dynamic tables for scheduled and incremental processing.
At least 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 skills.
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 handling late-arriving data and backfills.
Experience writing unit and integration tests for data pipelines.
Production ownership experience covering 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, with appropriate verification for security, correctness, and maintainability.
Must be currently authorized to work in the United States; iSpot cannot sponsor or take over sponsorship of an employment visa for this position.

Nice To Haves

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.

Responsibilities

Build, tune, and maintain large-scale batch Spark pipelines that transform 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 involving file and API deliveries, identity matching, privacy-sensitive data handling, and delivery SLAs.
Build data-quality checks, reconciliation, telemetry, and alerting; handle late-arriving data and backfills.
Write and review technical designs and test plans, and lead small-to-medium projects from ambiguous requirements through production.
Own releases and deployments to team standards, including staged rollouts and rollback.
Participate in the team’s on-call rotation, 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 their output.