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iSpot.tv

TV ad attribution with real-time analytics

Software Engineer 3

Data EngineeringConfirmed live in the last 24 hours
Full-time$117.7k - $148.3k /yr

About the Job

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 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.
  • Applicants must be currently authorized to work in the United States; employment visa sponsorship or transfer is unavailable.

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, 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.

Desired Qualifications

  • 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.

About the Company

iSpot.tv

TV ad attribution with real-time analytics

iSpot.tv measures TV advertising effectiveness by linking ads to real-world actions like online activity, store visits, and sales. It collects a catalog of TV ads, airings data, and data from 12 million opt-in Smart TVs to deliver real-time impression and attention metrics through a subscription platform that integrates with a client’s marketing tools. This differs from competitors by providing real-time, outcome-based analytics that connect TV exposure to actual business results, not just impressions, with seamless integrations for planning and optimization. The goal is to help disruptive brands maximize TV ad ROI by tracking outcomes, optimizing campaigns, and aligning TV plans with business objectives.

Company size
201-500
Company stage
Growth Equity (Venture Capital)
Total funding
$382.8M
Headquarters
Bellevue, WA
Founded
2012

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