Senior Software Engineer II, Ads Data Solutions Engineering
New
CanadaFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 8+ years
- Required Skills
- PythonRubySnowflakeAirflowGogRPCSparkRESTful APIsdbtDatabricks
Requirements
- 8+ years of software engineering experience, with a strong focus on backend systems, data platforms, or large-scale distributed systems.
- Strong proficiency in Python and experience with an additional backend language such as Go or Ruby.
- Extensive experience building APIs and service-oriented architectures using REST or gRPC.
- Hands-on expertise with data engineering tools such as DBT, Airflow, Spark, Databricks, and advanced SQL optimization.
- Experience working with cloud data platforms such as Snowflake and AWS in production environments.
- Strong understanding of ad-tech ecosystems, including measurement, attribution, identity resolution, and cleanroom technologies.
- Familiarity with privacy and compliance frameworks such as GDPR and CCPA in data-driven systems.
- Experience with CI/CD, observability tools (e.g., Datadog), containerized systems, and production reliability practices including SLOs.
- Demonstrated ability to lead cross-team initiatives, influence technical direction, and communicate effectively with technical and non-technical stakeholders.
- Proven hands-on use of AI-assisted development tools and ability to apply AI effectively in engineering workflows.
Responsibilities
- Lead the design and evolution of scalable backend and data systems supporting off-platform advertising, cleanrooms, taxonomy automation, and measurement pipelines.
- Build and enhance data collaboration capabilities, including secure cleanroom orchestration, policy enforcement, and privacy-safe data sharing across partners.
- Develop and optimize large-scale data pipelines for ingestion, transformation, and analytics using modern data engineering frameworks and cloud infrastructure.
- Architect and maintain integrations with external advertising platforms, enabling identity resolution, attribution, and performance measurement at scale.
- Drive modernization of platform infrastructure, improving CI/CD, observability, reliability, cost efficiency, and system performance.
- Lead technical initiatives across teams, aligning stakeholders and defining reusable abstractions, standards, and engineering best practices.
- Mentor and support engineers, contributing to code reviews, design discussions, and overall engineering excellence.
- Champion AI-first engineering practices by integrating AI-assisted tools into design, development, testing, and documentation workflows.
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