Kumaran Systems: Engineering Future-Ready Transformations Since 1992, Kumaran Systems has been helping enterprises bridge the past and the future, reimagining legacy systems and embracing AI-led possibilities. With over 34 years of delivery excellence, we specialise in re-engineering core applications, driving cloud transformation, and building automation-first, GenAI-enabled ecosystems across the Banking and Financial Services, Insurance, Telecom, and Automotive sectors. We help organisations not just upgrade their systems but reimagine what’s possible.

Why Kumaran? We blend engineering discipline with AI innovation, helping clients modernise with confidence, automate with clarity, and scale with purpose. Our global delivery model ensures agility, responsiveness, and seamless collaboration, with clients always at the heart of every engagement. At Kumaran, we don’t just solve problems, we engineer future-ready transformations.

Job Description Role Overview We are looking for an ETL QA Engineer with strong experience inDatabricks and PySpark, combined with hands‑on exposure to AI‑assisted development and prompt engineering. The ideal candidate will be responsible for validating large-scale data pipelines, ensuring data quality, and leveraging tools like GitHub Copilot, GitHub Actions/Runners, and AI agents to improve testing efficiency and coverage. You will also contribute to building and validating AI‑powered knowledge bases.

Required Skills & Experience

CoreTechnical Skills

Strong hands‑on experience in

Databricks

(notebooks, jobs, clusters, Delta Lake, SQL).

Expert‑level

PySpark

skills, including transformations, actions, window functions, and optimization techniques.

Solid understanding of

ETL/ELTconcepts , data warehousing, and data modeling (star/snowflakeschemas, dimension/fact tables).





Proven experience in

datavalidation , data quality checks, and reconciliation techniques.

Practical experience with

GitHub ,

GitHub Copilot , and

GitHub Actions/Runners

for CI/CDpipelines.

AI &Prompt; Engineering

Experience crafting effectiveprompts for large language models (LLMs) for coding, testing, anddocumentation.

Exposure to

agent-basedarchitectures

or tools (e.g., workflow/agent frameworks thatorchestrate multi-step AI tasks).

Familiarity with AI-basedtools for code analysis, test generation, or knowledge management.

KnowledgeBase & Documentation

Experience building

AI-drivenknowledge bases

or documentation systems (e.g., using vector search,embeddings, or LLM-based retrieval).

Strong documentation skills,with the ability to translate complex data/QA concepts into clearknowledge articles.

Testing & QA Practices

Strong understanding of QAmethodologies: test planning, test design, defect management, and regression testing.

Experience with automated testing frameworks (Python-based testing libraries such as pytest , unittest , or similar).

Familiarity with data qualitytools/practices (e.g., validation rules, thresholds, anomaly detection).

Key Attributes

Strong analytical andproblem‑solving skills with a detail-oriented mindset.

Passion for data quality,automation, and continuous improvement.

Ability to work in an agile,fast‑paced workplace and collaborate across multiple teams like Businessand operations team and AD team.

Curiosity and openness to adopting new AI tools andpractices for QA.

Kumaran Systems is an Equal Opportunity Employer and does not discriminate on the basis of race or ethnicity, religion, sex, national origin, age, veteran disability or genetic information or any other reason prohibited by law in employment.

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📌 ETL QA (Toronto)
🏢 Kumaran Systems
📍 Toronto