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SeniorRemoteCanada

Data QA Developer

J
jobgether
Уровень
Senior
Формат
Remote
О роли

Описание вакансии

About the company

Our partner is looking for a Senior Data QA Developer based in Canada. This is a senior engineering role focused on ensuring the integrity, reliability, and scalability of modern data platforms.

Responsibilities
  • Design and architect robust, automated data quality frameworks and testing suites using Python and SQL to validate data integrity, schema consistency, transformation logic, and pipeline behavior.
  • Partner with Data Developers and Product Managers during solution design to establish data contracts, quality gates, acceptance criteria, and testing strategies before implementation begins.
  • Develop automated data-SLA monitoring and observability capabilities to identify anomalies and data quality issues across BigQuery, Airflow, and downstream systems.
  • Perform detailed validation of complex ELT/ETL processes, ensuring datasets are accurate, secure, reliable, and optimized for analytics and reporting workloads.
  • Integrate data-specific automated testing and regression checks into Git-based CI/CD pipelines and infrastructure-as-code workflows.
  • Investigate data defects, pipeline failures, anomalies, and SQL performance issues, identifying root causes and implementing durable solutions.
  • Collaborate with engineering teams to improve data modeling, documentation, governance, development workflows, and overall quality standards.
  • Contribute to continuous improvement initiatives that make data development, deployment, monitoring, and validation more efficient and reliable.
  • Help establish scalable QA practices and technical standards that support the growth of a modern cloud-based data platform.
Requirements
  • 5+ years of experience in Data QA, Data Engineering QA, or a closely related discipline, preferably within complex SaaS or cloud data environments.
  • Strong Python and SQL skills, with the ability to develop clean, maintainable, and scalable automated testing solutions.
  • Hands-on experience with modern data platforms, particularly GCP and BigQuery.
  • Practical experience with data orchestration technologies such as Airflow.
  • Strong understanding of ETL/ELT pipelines, data transformations, data validation, data modeling, and dimensional design.
  • Ability to analyze complex SQL execution plans and identify data or query performance bottlenecks.
  • Experience designing automated testing, data quality checks, regression testing, monitoring, or observability frameworks.
  • Familiarity with Git-based CI/CD environments and data testing integration into automated deployment workflows.
  • Experience with Pulumi or Terraform is a significant advantage.
  • Familiarity with data quality and observability tools such as Great Expectations, Monte Carlo, or comparable technologies is beneficial.
  • Strong analytical and problem-solving abilities, with a methodical approach to diagnosing data issues.
  • Self-driven and comfortable taking ownership in a fast-paced, high-growth environment where priorities may evolve quickly.
  • Strong communication and collaboration skills, with the ability to work effectively with data engineers, developers, product managers, and other stakeholders.
  • Bachelor’s or master’s degree in Computer Science, Software Engineering, or a related technical discipline.
Conditions
  • Competitive compensation and the opportunity to work with a high-performing technology team.
  • Employee mortgage program with access to preferred low rates.
  • 4 weeks of vacation per year.
  • Premium health and wellness benefits fully paid by the employer.
  • Annual wellness budget to support physical and mental well-being.
  • 24/7 telemedicine access.
  • Fully remote position open to candidates anywhere in Canada.
  • Opportunity to work on modern cloud data technologies and large-scale, business-critical data infrastructure.
  • Collaborative, entrepreneurial, and innovation-focused work environment.
  • Opportunity to contribute to the evolution of a modern data platform and establish data quality practices at scale.
  • Inclusive workplace committed to diversity, equity, inclusion, and belonging.
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