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Python Automation Testing Jobs in Nova Scotia (NOW HIRING)

The ideal candidate brings a strong testing mindset, hands-on automation skills, and the ability to ... Scripting or programming experience (e.g., Java, Python, JavaScript). * Exposure to API testing and ...

The ideal candidate brings a strong testing mindset, hands-on automation skills, and the ability to ... Scripting or programming experience (e.g., Java, Python, JavaScript). * Exposure to API testing and ...

... testing across the application lifecycle Leverage automation frameworks and tools to maximize test ... Python programming language Must be comfortable with Big Data skills including Hive and HQL (Hive ...

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Python Automation Testing information

What is the difference between Python Automation Testing vs Manual Software Testing?

AspectPython Automation TestingManual Software Testing
Required SkillsPython programming, automation tools, scriptingTest case execution, attention to detail, communication
Work EnvironmentAutomated testing frameworks, scripting environmentsTest labs, user environments, manual execution
Industry UsageSoftware development, QA teams, continuous integrationInitial testing phases, exploratory testing, user acceptance

Python Automation Testing involves writing scripts to automate test cases, increasing efficiency and repeatability. Manual Software Testing requires testers to execute test cases manually, focusing on exploratory and usability aspects. Both roles are essential in software quality assurance, but Python Automation Testing emphasizes automation skills, while manual testing emphasizes detailed test execution and observation.

What are the key skills and qualifications needed to thrive as a Python Automation Testing professional, and why are they important?

To thrive as a Python Automation Testing professional, you need strong proficiency in Python programming, knowledge of software testing methodologies, and experience with test automation frameworks, often supported by a degree in computer science or a related field. Familiarity with tools such as Selenium, PyTest, Jenkins, and version control systems like Git is typically required, along with certifications like ISTQB being advantageous. Analytical thinking, attention to detail, and effective communication skills help testers identify issues, collaborate with teams, and document findings clearly. These competencies ensure the creation of reliable, maintainable automated tests that improve software quality and streamline development cycles.

What are some common challenges faced in a Python Automation Testing role, and how can they be addressed?

One common challenge in Python Automation Testing is maintaining test scripts as applications evolve, which can lead to flaky tests or outdated scripts. To address this, it's important to implement modular and reusable code, and regularly review and refactor test cases. Collaborating closely with developers and participating in code reviews can also help testers anticipate changes and adapt their tests proactively. Additionally, integrating robust reporting and logging mechanisms helps quickly identify and resolve issues, ensuring the reliability of the automated test suite.

What is Python Automation Testing?

Python Automation Testing refers to the process of using Python programming language to write scripts that automatically test software applications. These scripts can validate functionality, performance, and reliability of software, reducing the need for manual testing and speeding up the development cycle. Python is popular for automation testing because of its readability, extensive libraries like Selenium and PyTest, and strong community support. Automation tests can be integrated into continuous integration pipelines to ensure consistent quality across software releases.
What job categories do people searching Python Automation Testing jobs in Nova Scotia look for? The top searched job categories for Python Automation Testing jobs in Nova Scotia are:
BigData Quality Engineer

Full-time

Posted 19 days ago


Job description

Job Description

What's the opportunity?
As part of the Global Functions Technology (GFT) within RBC's Technology and Operations division, you'll be at the heart of a team that extends its services across the organization, offering IT solutions that drive transformation and efficiency. Our collaborative efforts span various domains including Risk, Finance, HR, CAO, Audit, Legal, Compliance, Financial Crime, Capital Markets, Personal and Commercial Banking, and Wealth Management. Moreover, we're at the forefront of creating digital tools and platforms that foster better collaboration across the board.

In this dynamic environment, you'll have the opportunity to work closely with leadership that values the recognition of achievements and the sharing of insights across teams to fuel continuous improvement.

Joining our Finance IT Data As a Service team, you'll play a supporting role in Test Implementation and Test Automation on our cutting-edge Big Data Platform. This role involves working with the latest technologies and programming languages such as Cloudera, Spark, Scala, Unix, SQL, Python, Databricks, and leveraging GenAI and Agentic AI.

Your primary responsibility will be to support QE Automation for our diverse client groups - executing tests, building automation scripts, and validating data pipelines under the guidance of senior engineers. This position offers a unique chance to develop your technical expertise in big data testing, finance data, and AI-driven quality engineering, all while delivering IT solutions in a fast-paced and ever-changing business landscape.

What you will do?

  • Execute test cases for data pipelines from ingestion to consumption, validating transformations, aggregations, and business rules across HDFS, Hive, Spark, and Databricks.

  • Validate ETL/ELT logic using Python (PySpark) and SQL - joins, filters, lookups, derived columns, and data mappings; perform source-to-target reconciliation.

  • Develop and maintain automated test scripts using AI, Python (Pandas, PySpark) and SQL

  • Contribute to automated test suites with CI/CD integration (GitHub Actions, Ansible Automation Platform; automate schema validation, row count checks, and data comparisons across environments.

  • Execute data quality checks - completeness, accuracy, consistency, and timeliness - on finance datasets

  • Test Spark jobs, Hive queries, and Data Lake pipelines; validate data landing, partition management, file integrity, and data freshness.

  • Leverage Generative AI tools (GitHub Copilot, Windsurf) to accelerate test case generation, SQL writing, and script development; support building Agentic AI workflows for autonomous test execution and intelligent triage.

  • Validate data feeding into ML models and test AI-generated outputs for correctness; support feature store and training data quality validation.

  • Understand and test finance data attributes: Trades, booking entities, currencies, GL accounts, product types, settlement dates; support regulatory and management reporting feed validation.

  • Partner with data engineers, SRE, and product teams to support testability and observability; log defects with clear root cause analysis in JIRA; maintain test documentation in Confluence.

  • Participate in Agile/Scrum ceremonies and contribute to shift-left testing practices and continuous testing workflows.


What you'll impact

  • Reliability and accuracy of critical data processing that powers Finance, Risk, Audit, Compliance, and enterprise reporting.

  • Faster, predictable releases through standardized automation, early validation, and AI-enabled quality acceleration.

  • Reduced operational risk via proactive defect prevention, audit-ready artifacts, and governance-aligned controls.

What you'll need to thrive

Must-Haves

  • 1-2 years hands-on experience in QE, data testing, or data engineering in Big Data environments.

  • Strong foundation: Bachelor's degree in Computer Science, Engineering, Finance, or equivalent experience.

  • SQL proficiency: Spark SQL, Databricks SQL, Hive, Trino - writing and debugging queries for data validation and reconciliation.

  • Code & scripting: Python (PySpark, Pandas), Shell scripting, SQL; ability to build and maintain automated test scripts.

  • Big Data fundamentals: HDFS, Hive, Parquet, Spark; understanding of data pipelines

  • Databricks: Experience with notebooks, Delta Lake, Databricks SQL, and basic workflow execution.

  • Testing fundamentals: Test case design, defect lifecycle, regression testing, integration testing, source-to-target validation.

  • Generative AI: Practical use of GitHub Copilot or similar AI assistants; prompt engineering for test generation and SQL writing; awareness of Agentic AI concepts.

  • Finance data awareness: Basic understanding of positions, valuations, products, currencies, booking entities, and reporting feeds (or strong willingness to learn quickly).

  • DevOps/toolchain: JIRA, Git, Confluence, Linux command line; familiarity with CI/CD concepts.


Nice to have

  • Experience with data governance, audit readiness, and privacy-preserving testing.

  • Exposure to test automation frameworks (Robot Framework, pytest, Selenium) and CI/CD pipelines (GitHub Actions, Jenkins, UrbanCode Deploy).

  • AI/ML ops exposure: dataset curation, validation, synthetic data generation for tests.

What's in it for you?

  • We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

  • A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable

  • Leaders who support your development through coaching and managing opportunities

  • Ability to make a difference and lasting impact

  • Work in a dynamic, collaborative, progressive, and high-performing team

  • Opportunities to do challenging work

  • Opportunities to take on progressively greater accountabilities

#LI-ASPOST

Job Skills

Application Testing, Decision Making, Detail-Oriented, Group Problem Solving, IT Quality Assurance, Long Term Planning, Predictive Analytics, Programming Languages, Software Product Testing, Test Automation

Additional Job Details

Address:

175 WESTERN PKY:BEDFORD

City:

Bedford

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-06-01

Application Deadline:

2026-06-29

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Employment Type: FULL_TIME