This position is listed on behalf of a partner company, who manages all applications and next steps. 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. You’ll design and build automated quality frameworks that validate complex pipelines, transformations, schemas, and datasets. Working closely with data engineers and product stakeholders, you’ll help embed quality controls early in the development lifecycle. You’ll work hands-on with Python, SQL, BigQuery, Airflow, and modern CI/CD practices to create dependable data products. The role offers significant ownership in a fast-moving, technology-driven environment where engineering quality directly impacts business-critical analytics. It’s an opportunity to help establish data quality standards and build resilient infrastructure within a high-growth organization.
Accountabilities:
- 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.
Benefits
- 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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
#LI-CL1
