> Markdown version of [/jobs/ext/3976576-software-development-engineer-3](https://www.wearedevelopers.com/jobs/ext/3976576-software-development-engineer-3). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Software Development Engineer 3

- **Company:** iSpot.tv, Inc.
- **Location:** Bellevue, WA, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $117,688.0 - $148,289.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon S3, Apache HTTP Server, Code Review, Continuous Integration, Information Engineering, Data Security, Relational Databases, Python (Programming Language), MySQL, Software Tools, SQL Databases, Systems Integration, Data Processing, Sql Optimization, Snowflake, Apache Spark, Pyspark, Integration Tests, Kubernetes, Data Pipelines
- **Published:** October 27, 2026
- **Apply:** https://startup.jobs/software-development-engineer-3-ispottv-10559344

## About the Role

* 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.

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.

## Description

* 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.