Data Platform QA Engineer (Data Quality & Observability)

Having recognized the advantages of remote work, including employee morale, productivity, reduced commuting on employee wellbeing and the environment, we are proud to be a digital-first company. The technologies and programs in which we invested have provided a fantastic foundation to this end. Our digital-first work environment, together with our conveniently located offices and collaborative workspaces, provide our team with the freedom and flexibility to work in the way that makes our employees most productive.

About us

Tecsys is a fast-growing innovator offering supply chain solutions to industry leading healthcare systems, hospitals, and pharmacy businesses to distributors, retailers, and 3PLs. We work with industry leaders to transform their supply chains through technology. If you thrive on tackling interesting challenges with continuous learning opportunities, then Tescys could be a good fit for you!

About the Role

We're looking for a Data Platform QA Engineer (Data Quality & Observability) to join our TecsysIQ Data & AI team. This role is focused on ensuring the quality, reliability, and integrity of our cloud-based data platform built on Databricks and AWS.

This is not a traditional software QA role . You'll be responsible for validating data pipelines, transformations, and business rules across our data platform while partnering closely with Data Platform Developers and Product Owners. A key part of the role is embedding automated testing into the development lifecycle to ensure trusted, high-quality data for analytics and AI. You'll help ensure the quality of the data powering analytics, reporting, and AI solutions used by healthcare organizations worldwide.

Responsibilities

• Design and develop automated tests for Databricks data pipelines and transformations.
• Validate end-to-end data movement across Bronze, Silver, and Gold data layers.
• Create SQL and Python-based validation scripts to verify data quality and business rules.
• Build and maintain automated regression test suites for data pipelines.
• Integrate automated testing into CI/CD pipelines.
• Implement data observability checks, including schema validation, data freshness, volume monitoring, and anomaly detection.
• Investigate data quality issues, perform root cause analysis, and support production releases.
• Collaborate with Data Platform Developers, Product Owners, and business stakeholders in an Agile environment to ensure high-quality data products.

Qualifications

• Hands-on experience with Databricks (mandatory).
• Experience testing data platforms, ETL/ELT pipelines, data lakes, or data warehouses.
• Strong SQL skills for data validation, analysis, and troubleshooting.
• Experience developing test automation using Python.
• Experience with test automation frameworks and CI/CD pipelines.
• Understanding of data quality, business rule validation, and data observability concepts.
• Experience working in Agile teams alongside Data Platform Developers and Product Owners.
• Strong analytical, problem-solving, and communication skills.

We understand that experience comes in many forms and that careers are not always linear. If you don't meet every requirement in this posting, we still encourage you to apply.

At Tecsys, we are committed to fostering a diverse and inclusive workplace where all employees feel valued, respected, and empowered. We believe that diversity drives innovation and strengthens our ability to deliver exceptional solutions. We welcome and encourage applicants from all backgrounds, experiences, and perspectives to join our team.

Tecsys is an equal opportunity employer. Accommodation is available for applicants selected for an interview.

NB: if you are applying to this position, you must be a Canadian Citizen or a Permanent Resident of Canada, OR , have a valid Canadian work permit.

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A Note on Our Hiring Process: We do not use AI to automatically screen or reject candidates. However, we do use specific screening questions to prioritize the most relevant applications for human review.

During interviews, we expect candidates to engage without the use of AI tools, scripts, or real-time assistance. Authentic, direct conversation helps us get to know how you think, collaborate, and communicate. AI can support your preparation, but it shouldn’t speak or act on your behalf. We genuinely want to meet  you .