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Ads Data Engineer

Canada, Toronto · Job Posted February 21, 2026
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Job Description

As the foundational Data Engineer for HTS Media, you will own the data infrastructure that powers our entire advertising business. Our platform generates a massive volume of data, from ad impressions and clicks to audience segments and conversion events, that is critical to our advertisers, partners, and internal teams. Your mission is to build a robust, scalable data foundation from the ground up that transforms this raw data into the trusted, high-quality datasets that power our advertiser-facing reporting and enable our future ML models. You will be responsible for the full lifecycle of data, from building real-time data pipelines to modeling data in our warehouse for analytics and reporting. You will partner closely with backend, full-stack, and product teams to power fast, accurate, and reliable reporting that will build advertiser trust. You will lay the groundwork for our ML optimization engine, which will drive ad-serving predictions (like CTR and conversion rates) to make our platform smarter and more performant—mirroring the successful data-driven ad platforms at companies like Amazon and Instacart. Your work will be the foundation of our platform's intelligence and a key factor in our ability to deliver measurable results.

Job Responsibility

  • Own the Data Architecture: Design, build, and maintain scalable and reliable ETL/ELT pipelines to process high-volume advertising data
  • Build the Foundation: Develop and manage our analytical data warehouse, establishing it as the single source of truth for all reporting and analytics
  • Enable Insights: Create clean, reliable, and performant data models that power our advertiser reporting dashboards, internal analytics, and billing systems
  • Ensure Data Integrity: Implement robust data quality checks, monitoring, and alerting to ensure the accuracy and trustworthiness of our data
  • Collaborate and Empower: Work closely with the engineering and product teams to define data requirements and deliver the necessary data infrastructure to support new ad products and features
  • Prepare for the Future: Build the foundational data systems that will enable future ML-driven optimizations for audience targeting and performance prediction

Requirements

  • 4+ years of data engineering experience, with a demonstrated track record of building and maintaining data infrastructure at scale
  • Expert-level proficiency in SQL and a programming language like Python or Scala for data processing
  • Hands-on experience with cloud-based data warehousing solutions (e.g., BigQuery, Snowflake, Redshift)
  • Proven success building and operationalizing data pipelines using orchestration tools (e.g., SQLMesh, Airflow, dbt)
  • Experience with real-time data streaming technologies (e.g., Google Pub/Sub, Kafka, Kinesis)
  • Strong understanding of data modeling concepts and experience designing schemas for analytical workloads
  • Experience with ad tech, retail media, or large-scale data systems is strongly preferred
  • Excellent communication skills and an ability to collaborate effectively with both technical and business stakeholders
  • A strong sense of ownership and the ability to operate with a high degree of autonomy in a fast-paced, entrepreneurial culture

What we offer

  • Well-funded and proven startup with large ambitions, competitive salary and upsides of pre-IPO equity packages
  • Hopper covers 100% of the premiums for group insurance plan
  • Hopper offers life, short term and long term disability coverage
  • HSA that covers eligible medical and dental expenses
  • All employees and dependents have access to Dialogue’s telemedicine services, anytime, anywhere
  • All employees have access to an RRSP plan with automatic pre-tax withdrawals per pay
  • Very generous parental leave, much above industry standards
  • Unlimited PTO
  • Carrot Cash travel stipend
  • Access to co-working space on demand through FlexDesk AND Work-from-home stipend
  • Entrepreneurial culture where pushing limits and taking risks is everyday business
  • Open communication with management and company leadership
  • Small, dynamic teams = massive impact

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