Senior Data Engineer, Ads Data (AI Native)
New
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JobgetherAdvertising technology
Remote-first working environment across Canada.Full-TimeSenior
SalaryAnnual base salary range for Canada: $149,500–$177,500 CAD. Additional equity compensation through Restricted Stock Units (RSUs).
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Job Details
- Experience
- At least 5 years of professional data engineering experience
- Required Skills
- AWSPythonSQLSparkTerraformScaladbtDatabricksPySpark
Requirements
- Bring at least 5 years of professional data engineering experience building and maintaining production-grade data platforms at enterprise scale.
- Have advanced hands-on Apache Spark expertise, including PySpark or Scala, and knowledge of partitioning, joins, shuffle behavior, caching, skew management, and performance optimization.
- Have deep Databricks knowledge, including Delta Lake, Unity Catalog, Jobs and Workflows, Databricks Asset Bundles, Structured Streaming, and SQL Warehouses.
- Be proficient in SQL and Python or Scala for pipeline development, automation, and query optimization.
- Have practical dbt experience with data modeling, incremental strategies, testing, documentation, and CI/CD integration.
- Have hands-on Terraform and AWS experience, particularly with S3, IAM, and cloud infrastructure fundamentals.
- Have experience with orchestration such as Airflow or Databricks Workflows, Git, CI/CD pipelines, and production monitoring.
- Understand data architecture and modeling principles, including dimensional modeling, star schemas, medallion architecture, and semantic layers.
- Have experience improving pipelines and data models while maintaining reliability, scalability, maintainability, and backward compatibility.
- Have used AI coding assistants such as Claude, Cursor, or GitHub Copilot for substantive engineering tasks, and be able to review, test, and own AI-generated code.
- Hold a bachelor's degree in Computer Science, Engineering, or a related discipline, or have equivalent professional experience.
- Be familiar with data governance, privacy, and compliance standards, including GDPR, CCPA, and SOX.
Responsibilities
- Enhance, maintain, and scale batch and streaming pipelines, Delta Lake tables, and data workflows using Databricks.
- Collaborate with analysts, advertising strategists, and sales teams to turn business requirements into reliable datasets, reporting solutions, and insights.
- Develop and maintain dbt models, automated tests, semantic layers, and standardized business metrics.
- Optimize Spark and Databricks workloads through query optimization, partitioning, cluster configuration, and resource allocation.
- Maintain data platform infrastructure using Terraform and AWS.
- Implement monitoring, data lineage, SLAs, alerting, access controls, and data contracts to support data quality and governance.
- Establish engineering practices for version control, CI/CD, testing, documentation, and code reviews; mentor colleagues and contribute to technical roadmap decisions.
- Integrate data from advertising platforms, CRM systems, external partners, and internal applications, including migrations from legacy reporting tools.
- Develop tools, workflows, and AI agents that provide LLMs with relevant context and accelerate development, debugging, and system maintenance.
- Improve foundational pipelines and models, reduce processing times and infrastructure spending, and increase self-service access to business information.
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