Software Development Engineer 3

• 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.

• 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.
• Advanced SQL and relational data modeling.
• Experience building external partner or client data feeds that involve 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.

• 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.

Target cash compensation range: $117,688 - $148,289 USD Annually

We are committed to providing competitive, market-informed compensation. The cash compensation above includes base salary, variable commission for employees in eligible roles, and annual bonus targets for eligible roles. In addition to cash compensation, all full time iSpotters are eligible to participate in iSpot’s equity plan to receive stock options. Non-exempt roles will also be eligible for (pre-approved) overtime pay. Individual compensation packages are influenced by different factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons.

For more information on total rewards package, go HERE

Hybrid & Flexible Workplace Policy

iSpot supports a hybrid and flexible workplace. Depending on location and work responsibilities, employees may be designated as full-time or part-time office-based or a fully remote employee. A hybrid work schedule indicates that you work in the office some days and work from home other days. The best hybrid workplaces allow for flexibility while also encouraging consistency. 

Those local or living in surrounding areas to one of our offices (Bellevue, WA or New York, NY) will work a hybrid schedule, coming into their local office 1-3 days a week. While those in a role, not office-based and located further away from our offices, will work a fully remote schedule. If you have questions regarding exact details of our hybrid & flexible workplace policy, please let your recruiter know and they will discuss with you further.

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