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Data Validation Engineer Jobs in Ontario (NOW HIRING)

Develop automated validation and reconciliation processes to ensure data accuracy. * Convert SAS ... Advanced SQL and data engineering expertise. Experience building scalable, high-performance data ...

Senior Data Analyst

Toronto, ON · Hybrid

CA$105K - CA$115K/yr

You work closely with consultants, data engineers, developers, designers and clients across ... Lead analytical projects end-to-end including discovery, data validation, analysis, and ...

Lead application support initiatives as a Production Support Engineer focused on banking ... analysis, data validation, and efficient scripting capabilities. Collaborating with cross ...

New

The Manager, Model Validation provides independent, objective assessment and effective challenge of ... engineering, finance, or data science) or equivalent experience. * 2-3 years of relevant experience ...

Be Seen First

Execute discovery runs and validate data collection across 15,000+ servers and network devices * Implement cloud vendor infrastructure discovery and integration (up to 1 supported cloud provider)

New

Data Engineer

Concord, ON

CA$90K - CA$150K/yr

The Data Engineer is responsible for designing, building, and maintaining the data pipelines and ... Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of ...

Data Engineer

Markham, ON

CA$90K - CA$150K/yr

The Data Engineer is responsible for designing, building, and maintaining the data pipelines and ... Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of ...

Be Seen First

Execute discovery runs and validate data collection across 15,000+ servers and network devices * Implement cloud vendor infrastructure discovery and integration (up to 1 supported cloud provider)

New

Data Engineer

Guelph, ON

CA$90K - CA$150K/yr

The Data Engineer is responsible for designing, building, and maintaining the data pipelines and ... Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of ...

Data Engineer

Kitchener, ON

CA$90K - CA$150K/yr

The Data Engineer is responsible for designing, building, and maintaining the data pipelines and ... Implement data quality, validation, and lineage controls to ensure accuracy and trustworthiness of ...

Data Engineer

Toronto, ON · Remote

CA$140K - CA$190K/yr

Overview The Data Engineer on the Nebula team plays a critical role in building and evolving the ... Implement data quality checks, validation rules, reconciliation processes, and monitoring to ensure ...

Data Engineer, Data Platform

Toronto, ON · On-site

CA$85K - CA$100K/yr

This is a hands-on engineering role for someone who thrives in code, designing and delivering high ... Implement data quality, validation, observability, and lineage controls to meet enterprise ...

Monitor data pipeline health, investigate data quality issues, assess their impact, and validate ... to data engineering * Contribute to process improvements, documentation, and knowledge sharing ...

Monitor data pipeline health, investigate data quality issues, assess their impact, and validate ... University degree in Engineering, Math, or Computer Science * 2+ years of full-time and/or ...

Monitor data pipeline health, investigate data quality issues, assess their impact, and validate ... University degree in Engineering, Math, or Computer Science * 2+ years of full-time and/or ...

Company Description Are you a Data Engineer with experience building cloud-based data solutions and ... Build automated validation, deduplication, masking, encryption and column‑level security to ...

Showing results 41-60

Data Validation Engineer information

What is a data validation engineer?

Data Validation Engineers are professionals responsible for ensuring the accuracy, quality, and integrity of data within software systems or databases. They design and implement tests, validation protocols, and automated processes to verify that data meets specified requirements and is free from errors. Data Validation Engineers often work closely with data engineers, analysts, and developers to identify inconsistencies, troubleshoot issues, and maintain reliable datasets crucial for business operations and decision-making.

What are the key skills and qualifications needed to thrive as a data validation engineer?

To thrive as a Data Validation Engineer, you need strong analytical skills, a background in computer science or engineering, and experience with data quality assurance methodologies. Familiarity with database management systems, data validation tools (like Talend or Informatica), and scripting languages such as Python or SQL is typically required. Attention to detail, problem-solving abilities, and effective communication are critical soft skills in this role. These competencies are essential for ensuring data integrity, minimizing errors, and supporting reliable business decision-making.

What are the typical challenges faced by data validation engineers when working with large and complex datasets?

Data Validation Engineers often encounter challenges such as handling inconsistent data formats, ensuring data integrity across multiple sources, and managing large-scale datasets efficiently. Identifying subtle data anomalies and implementing robust automated validation scripts can be difficult, especially when data is unstructured or rapidly changing. Collaboration with data engineers, analysts, and quality assurance teams is essential to develop effective validation strategies and maintain high data quality standards throughout the data pipeline.

What is the difference between Data Validation Engineer vs Data Analyst?

AspectData Validation EngineerData Analyst
Primary FocusEnsuring data accuracy, integrity, and validation processesAnalyzing data to identify trends and generate reports
Skills & CertificationsData validation tools, SQL, scripting, quality assuranceData analysis, visualization, statistical skills, Excel, SQL
Work EnvironmentData warehouses, ETL pipelines, quality assurance teamsBusiness units, reporting teams, data-driven departments
Industry UsageTech, finance, healthcare, where data quality is criticalMarketing, finance, consulting, where insights drive decisions

While both roles work with data, Data Validation Engineers focus on verifying data accuracy and integrity during data processing, whereas Data Analysts interpret data to provide insights and support decision-making. Understanding these differences helps organizations assign the right skills to each role.

What cities in Ontario are hiring for Data Validation Engineer jobs?

Cities in Ontario with the most Data Validation Engineer job openings:

Infographic showing various Data Validation Engineer job openings in Ontario as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution.

Senior Engineer, Data Enablement, Data Platforms

Toronto, ON • On-site

Full-time

Re-posted 19 days ago


Key responsibilities

  • Build and support Data Enablement services and platform components to improve data discovery, access, and self-service experiences

  • Collaborate with users and stakeholders to gather feedback and refine features to ensure solutions are practical and adopted

  • Build and maintain backend services and APIs that support enterprise data platforms and portals


Job description

Purpose.Performance. People.

Joining CPP Investments means joining one of the world's most admired and respected institutional investors to drive a single mandate: to deliver strong, sustainable returns for generations of Canadians.

With a long-term horizon and global reach, we deploy capital at scale across public and private markets. Our size, stability, and disciplined investment philosophy allow us to pursue complex opportunities and build enduring partnerships worldwide.

For our people, this means meaningful work with tangible impact, real opportunity, and collaboration with exceptional colleagues who value partnership and performance. Here,you'llcontribute to outcomes that matter alongside team members committed to excellence and shared success.

Role Summary:

The Data Enablement Team enables the organization to derive value from enterprise data by building reusable platforms, tools, and services that help users and applications discover, understand, and safely consume trusted data products for production, analytics, and research use cases. The team owns the enterprise Data Portal and the FinSights BI Portal (one-stop shop for enterprise BI assets), builds lowlatency consumption services on top of the Enterprise Data Fabric and data catalog, and delivers product governance services, operational dashboards, and computational governance embedded into the platform. The team uses automation and agentic techniques as implementation tools to improve discovery, comprehension, and selfserve user journeys across departments-while maintaining security, entitlements, and policy controls by design.

Accountabilities & Qualifications:

Accountabilities

  • Build and support Data Enablement services and platform components to improve data discovery, access, and self-service experiences
  • Collaborate with users and stakeholders to gather feedback and refine features to ensure solutions are practical and adopted
  • Develop solutions with performance, scalability, resiliency, and security in mind, following DevSecOps and operational standards
  • Contribute to solution design and documentation (e.g., LLD, interface specifications) and support governance processes (ARB, Information Security)
  • Partner with Cloud Foundation and Data Foundation teams to integrate with shared services, entitlements, and platform standards
  • Build and maintain backend services (serverless and containerized where appropriate) that support enterprise data platforms and portals
  • Implement and maintain APIs, including contracts, versioning, and data validation
  • Contribute to workflow automation capabilities within Data Enablement solutions under enterprise controls

Qualifications

  • 5+ years of software engineering experience delivering production-grade services using Python
  • Strong experience with AWS cloud platform, including networking and secure access patterns
  • Solid understanding of identity and access management (IAM, authentication/authorization patterns)
  • Experience building backend services and APIs (REST/GraphQL, event-driven architectures, resiliency patterns)
  • Hands-on experience with Infrastructure-as-Code and DevSecOps practices (e.g., Terraform, CI/CD, security controls)
  • Experience with observability and reliability practices (monitoring, alerting, incident response)
  • Strong API design experience (OpenAPI/Swagger, versioning, backward compatibility)
  • Experience working with structured data formats and schema processing (e.g., JSON)
  • Working knowledge of authentication and authorization patterns (e.g., Cognito, IAM)

Nice to have

  • Experience with agentic or orchestration frameworks (e.g., AWS Bedrock, LangChain, LlamaIndex)
  • Understanding of retrieval approaches such as RAG and GraphRAG
  • Experience with vector search technologies (e.g., OpenSearch, Pinecone, Weaviate)
  • Familiarity with containerization and platform operations (e.g., Docker, Kubernetes/EKS)
  • Experience integrating with enterprise data platforms, catalogs, or governed access patterns
  • AWS Data & Analytics certification; ML-related certification is a plus

#INDGD-T


You are motivated to contribute to something larger than yourself, approach complex challenges with rigor, and hold yourself tohigh standardsin a collaborative, performance-driven environment.


We provide colleagues with cutting-edge AI tools, dedicated learning time, and practical support to help them deliver with greater impact.

Inclusion & Accessibility

CPP Investments is committed toequitableaccess to employment and building a workforce that reflects diverse talent and perspectives. If you require accommodation at any stage of the recruitment process, please let us know and we will work with you to meet your needs.

Attention: Protect Yourself from Fraud

CPP Investments is committed to a secure and transparent recruitment process. We will never ask candidates for payment or financial information at any stage of hiring. All legitimate opportunities are posted on our careers page, and communications will come from our applicant tracking system, Workday.


CPP Investments may use AI tools to help screen and assess applicants by analyzing resumes and applications for relevant skills and experience. These tools support, but do not replace, human decision-making.


#LI-ONSITE