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Added 11 mins ago
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Test Engineer (ETL/Cloud Migration)
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Toronto, ON
Full-time
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Software Quality Assurance (SQA) Engineer - EN 368
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Added 5 hours ago
Software Quality Assurance (SQA) Engineer - EN 368
Export Development Canada | Exportation et développement Canada
Remote, Canada
Full-time · Remote
Position: Software Quality Assurance (SQA) Engineer (Level 17) – Quality & Automation Focus
Added 5 hours ago
Software Quality Assurance (SQA) Engineer - EN 368
Export Development Canada | Exportation et développement Canada
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Full-time · Remote
Position: Software Quality Assurance (SQA) Engineer (Level 17) – Quality & Automation Focus

Next Pathway

Test Engineer (ETL/Cloud Migration)

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 28, 2026
Posting language: English
Posted: Sep 28, 2026

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Original job description

Test Engineer (ETL/Cloud Migration)

for

Next Pathway - The Automated Cloud Migration Company

Cloud Migration Validation, Failure Triage & Root-Cause Analysis

The Role. Next Pathway is looking for technically strong, highly analytical Test Engineers who can investigate failures across complex cloud migration and data environments. This is not a traditional QA role: the engineer is expected to read logs, interrogate data, reproduce issues, isolate root causes, and determine whether a failure originates in code, data, configuration, environment, orchestration, permissions, or the test framework itself.

Location. Toronto

Key Responsibilities

Execute, monitor, and assess automated and manual testing for enterprise cloud migration and modernization workloads.
Use Next Pathway’s TESTER software to validate translated code, data integrity, execution results, and production readiness across source and target environments.
Analyze test results, application logs, database logs, ETL/orchestration logs, audit logs, stack traces, and execution errors to triage failures and isolate root causes.
Differentiate failures caused by translated-code defects, source or target data issues, environment instability, configuration, permissions, dependencies, orchestration, or test setup.
Write advanced SQL to validate transformations, reconcile source-to-target results, investigate row-count and aggregate differences, identify nulls/duplicates, and trace data-quality issues.
Use Python to parse logs, analyze datasets, automate investigations, build lightweight test utilities, and accelerate recurring diagnostic tasks.
Work with SHIFT outputs and migration engineering teams to reproduce and investigate translated-code failures and support rapid defect resolution.
Document defects with clear evidence, root-cause findings, ownership, impact, and recommended next actions; identify recurring patterns and improve test coverage and automation.

Core Technical Skills

Advanced SQL: complex joins, aggregations, CTEs, window functions, data reconciliation, schema/data-type analysis, and query-based troubleshooting.
Python: scripting, data manipulation, log parsing, automation, diagnostics, and test utility development.
Log & failure analysis: ability to navigate large volumes of technical logs, follow execution paths, correlate events, and identify the true failure point.
Data validation & reconciliation: source-to-target comparison, transformation validation, row counts, aggregates, schema checks, business-rule validation, and discrepancy analysis.
Databases & data pipelines: solid understanding of tables, views, stored procedures, schemas, constraints, transactions, ETL/ELT pipelines, dependencies, and scheduling/orchestration.
Cloud data platforms: experience with Snowflake strongly preferred; familiarity with Databricks and major cloud platforms is an asset.
Engineering toolchain: working knowledge of Git/GitHub, CI/CD pipelines, Linux/Unix command-line tools, APIs/JSON, and defect-management systems.
Performance troubleshooting: ability to recognize query, resource, timeout, dependency, and scalability issues that affect test execution.

What We Look For

Exceptional analytical, troubleshooting, and root-cause analysis skills; able to work methodically through ambiguous failures.
Systems thinking: understands that a failed test may originate anywhere across code, data, infrastructure, orchestration, configuration, permissions, or TESTER - and can determine which layer owns the issue.
Technical curiosity and independence: willing to dig into the evidence rather than simply escalate a failure.
Clear communication: can explain technical findings concisely to developers, data engineers, delivery teams, and client stakeholders.
Background may be in test engineering, data engineering, software engineering, or another technical discipline; diagnostic capability matters more than a traditional QA title.

What Success Looks Like

An average tester reports: “The test failed.” A strong Next Pathway Test Engineer explains why it failed, proves where the problem originated, identifies the likely owner, and provides the evidence needed to resolve it quickly.

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More about this job

Responsibilities

Execute and assess automated and manual tests for cloud migration workloads, validating translated code, data integrity, execution results, and production readiness. Investigate failures using SQL, Python, logs, and data comparisons; identify root causes, document evidence, and work with migration engineering teams to resolve defects.

Requirements

The role calls for strong SQL and Python skills, experience with data validation and ETL/ELT pipelines, and the ability to analyze logs and troubleshoot failures across code, data, infrastructure, configuration, and orchestration. Familiarity with Snowflake is strongly preferred, while Databricks, cloud platforms, Git/GitHub, CI/CD, Linux/Unix, APIs/JSON, and defect-management systems are assets.

Skills

Advanced SQL
Python
Log Analysis
Root-Cause Analysis
Data Validation
Data Reconciliation
ETL/ELT
Cloud Migration
Snowflake
Databricks
Git/GitHub
CI/CD
Linux/Unix
Test Automation
Performance Troubleshooting
Defect Documentation

Visa sponsorship

Not detected in the job text

Keywords

Cloud Migration
Next Pathway TESTER
ETL
ELT
SQL
Python
Snowflake
Databricks
Cloud Data Platforms
Data Validation
Data Reconciliation
Source-to-Target Comparison
Log Analysis
Root-Cause Analysis
Translated Code
Test Automation
Manual Testing
Data Integrity
Orchestration
Git
GitHub
CI/CD
Linux/Unix
APIs
JSON
Performance Troubleshooting
Database Logs
Audit Logs
Data Quality
Defect Management

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