Sr. IFRS17 Data Engineer (C#, SQL, MVC, WPF)
Toronto - Hybrid (4 Days WFO)
12 months


Job Description
Must have IFRS17 working experience with Data Analysis| Insurance domain knowledge
Good to have DATAIKU exposure Expert in Data Analysis| SQL| Python| PySpark
Develop and maintain backend systems using Python| PySpark ensuring high performance| scalability| and reliability
Participate in the design and implementation of data engineering and ETL pipelines using PySpark
Collaborate with cross-functional teams to identify and prioritize project requirements
Mentor and guide engineers| providing technical guidance and code reviews
Stay up-to-date with the latest technologies and frameworks| and apply this knowledge to improve existing systems and processes
Lead the technical direction of the team| including architecture| design| and implementation of software systems
Collaborate with product owners to define and prioritize requirements
Develop and maintain technical documentation| including architecture diagrams| and technical specifications
Participate in code reviews| ensuring high-quality code and adherence to coding standards
Collaborate with DevOps and Operations teams to ensure smooth deployment and operation of applications
Expert in DevOps practices and tools for CICD pipelines
Willingness to learn new technologies and adapt to new challenges
Proven experience in leading technical teams| including technical guidance| mentoring| and coaching
Strong technical leadership skills| including the ability to make technical decisions| prioritize tasks| and manage technical resources
Excellent communication and collaboration skills| with the ability to work effectively with cross-functional teams
Ability to drive technical innovation| including researching new technologies| evaluating technical options| and recommending technical solutions
Strong problem-solving skills| with the ability to debug complex issues| optimize system performance| and ensure high-quality software delivery
Experience with Agile development methodologies| including Scrum or Kanban| and the ability to apply these principles to lead the team
Experience with cloud platforms| including Amazon Web Services (AWS)| Microsoft Azure| or Google Cloud Platform (GCP)Experience with PySpark for Data EngineeringETL pipelines

We're looking for an experienced ETL and data engineering consultant to support enterprise data pipelines and cloud platform operations in Toronto. The ideal candidate brings strong SQL and Python skills, hands-on ETL experience, and a production-focused mindset for building and maintaining reliable data workflows.

What you'll do

• Build, maintain, and troubleshoot batch ETL pipelines with complex dependencies
• Perform advanced SQL transformations, debugging, and performance tuning
• Support data quality checks, reconciliation logic, and validation frameworks
• Work across source, staging, transformation, and target layers to perform deep-dive analysis
• Contribute to CI/CD pipelines and Git-based workflows for data engineering
• Collaborate with platform and delivery teams on cloud-based data infrastructure

What you bring

• 5+ years of experience with ETL tools such as Talend, Informatica, or Python-based pipelines
• Advanced SQL skills for complex transformations and performance tuning
• Hands-on experience with Snowflake and/or Databricks, preferably in AWS environments
• Working knowledge of Python for data processing, automation, or validation
• Solid understanding of data modeling — both relational and dimensional
• Familiarity with cloud security concepts including IAM and RBAC
• Experience with Docker and some exposure to Kubernetes-based deployments
• Experience with Git and CI/CD pipelines for data workflows
• Strong production mindset with attention to logging, alerting, monitoring, and failure recovery
• Eligibility for a mandatory background check

Nice to have

• Experience with CDC tools such as IBM CDC or Debezium
• Ability to read and interpret generated SQL, Java, or ETL tool metadata

Work setup

• Hybrid in Toronto, ON
• 12+ month contract
• English proficiency required

Role: SRE Lead
Duration: 12 months
Location: Toronto
Hybrid: 2 days in office a week

Deep application and system-level knowledge across complex end-to-end environments, including tightly integrated on prem and cloud native services, supporting large-scale, multitier transaction flows
Prior hands-on experience with APM and observability platforms, including Dynatrace or comparable enterprise observability tools, with the ability to instrument, analyze, and troubleshoot complex distributed applications
Proven deep troubleshooting experience resolving issues across multilayer, end to end (E2E) environments, spanning application, infrastructure, network, and platform layers across on prem and cloud services
The person is to drive and execute the SREWCCS Roadmap for Client
Hand-on role from day 1
Observability experience expectations please see description for Observability SME below
Deep knowledge and experience in implementing SRE practices and guiding complex SRE implementations across the industry
Would provide
o Assessments of current capability help identify gaps and contribute to the SRE WCCS roadmap
o Able to navigate multi-team SRE IT Ops to drive results
o Creative workaround and solutions
SRE Observability SME
Hands-on role from day 1
Day 1 Dynatrace expertise i.e.
o DQL
o Gen3 dashboards
o Traces on Grail
o Active-Gate Plugins
o SRG Workflow development
o Biz Events
Prior hands-on experience with APM and observability platforms, including Dynatrace or comparable enterprise observability tools, with the ability to instrument, analyze, and troubleshoot complex distributed applications
Deep troubleshooting expertise leveraging observability signals (metrics, events, logs, and traces) to identify root causes and resolve failures across multilayer E2E environments
Deep background on Observability fundamentals - MELT
Expert level Dashboard (related UIUX design)
Experienced in troubleshooting performance non-functional issues
Familiar with SRE concepts as outlined in Google SRE book workbook etc.
Expertise in AWS Observability, CW, Application Signals, Metrics, logs traces, Lambda, API-GW
Able to come up with creative ways to monitor observe systems like IBM Data power where sufficient observability isnt present
Development with Python, AWS Lambda, ECS, Azure Functions
Understands fundamentals of how AI based systems built and monitored
Background or knowledge of OTEL
Experienced in Financial Services are or equivalent i.e. very complex end-to-end transaction e.g. 50 systems working together to fulfil one customer request
Platform Engineering experience
Shipping platform capabilities (e.g., self-service onboarding pipeline, policy-as-code, golden signals-as-code, standardized instrumentation libraries).
Depth of knowledge for the role
Programming depth requires strong programming in Python and Node.js and building backend integrations components.
Looking for
Practically observability experience with multi-system integration
In-depth Observability

Looking for 8+ years candidate as Data analyst with capital markets and python experience 

• 3+ years of professional experience in Data Science
• Strong expertise in SAS (Base SAS, PROC SQL, SAS Macros, SAS/STAT, SAS/ETS, SAS Enterprise Guide)
• Strong Python experience for data science and modeling (Pandas, NumPy, Scikit-learn, Statsmodels, SciPy)
• Experience converting legacy SAS code to Python using Generative/Agentic AI tools
• Hands-on experience with AI coding assistants/LLM tools (Claude Code, GitHub Copilot, etc.)
• Strong understanding of statistical methods, business logic, and data transformations
• Experience with SQL and cloud/remote data platforms (AWS S3, SQL DBMS, etc.)
• Proficiency with Git and collaborative version control
• Experience performing code reviews, testing, and numerical validation of AI-generated code
• Ability to document conversion logic, statistical equivalencies, and deviations
• Experience identifying and escalating ambiguities in legacy code
• Strong collaboration skills working with data platform engineering teams
• Preferred experience in regulated industries (Pharma, Finance, Insurance, Government)
• Familiarity with UNIX environments
• Knowledge of credit risk models (PD, EAD, LGD) and IFRS9 requirements

We are looking for an experienced Databricks Data Engineer to join a data engineering team on a remote basis. You will maintain and enhance existing data pipelines that ingest data from mine operation sites in South America and make it available to business users through Databricks.

What you'll do

• Maintain and enhance data pipelines ingesting data from source systems at mine operation sites
• Load and manage data within Databricks using Delta Lake and Unity Catalog
• Build and support data transformations using DBT and SQL
• Ensure data is available and accessible for business users in a self-serve model
• Collaborate with stakeholders and teams across South America and Canada
• Support pipeline orchestration and monitor data flow across environments

What you bring

• Strong hands-on experience with Databricks
• Solid knowledge of Unity Catalog and Delta Lake
• Advanced SQL skills for data transformation and querying
• Experience with DBT for data modeling and transformation
• Experience designing and maintaining data pipelines and orchestration workflows
• Good communication and collaboration skills across global teams

Nice to have

• Experience with performance optimization in Databricks
• Proficiency in Python and PySpark
• Spanish language skills are a strong asset given collaboration with South American teams

Work setup

• 6 to 12 month contract
• Fully remote based in Vancouver, BC
• Mandatory background check required before onboarding

Title:- Control Test Analyst 

Location:- Toronto ON (Hybrid- 3 day’s onsite) Canada.

Fulltime

"Total Experience: 8-10 years
Role Description:
Execute IT General Controls (ITGC), application controls, and security controls testing across systems and platforms. 
Documentation: Prepare clear, detailed test plans, work papers, and evidence documentation. 
Deficiency Management: Assess root causes of control gaps, report on deficiencies, and track remediation plans to closure. 
Risk Evaluation: Assess control gaps for impact, risk exposure, and residual risk. Communication: Reporting Present assessment findings to management, stakeholders, and external auditors. 
Methodology Improvement: Suggest improvements for testing practices and increase automation of controls monitoring

Job Title: MS Data Fabrics Architect
Location: Toronto 
Work Type: Hybrid - Work from Office 3 days

Skills: Digital : Microsoft Power BI
Experience Required: 8-10

Role Descriptions:
Skill - Design and implement end-to-end data architectures leveraging Microsoft Fabric components One Lake| Lakehouse| Data Warehouse| Data Engineering| Data Factory| and Power BI with a strong emphasis on Medallion architectural patterns.

Data Modelling & Architecture:
Design and implement conceptual| logical| and physical data models.
Develop scalable and efficient data architectures using Azure Synapse and Databricks.
Integrate data from diverse sources including ERPs| APIs| and cloud databases.
Work closely with data engineers| analysts| and business stakeholders to gather requirements.
Derive Logical| Physical data models.
Ability to do reverse engineering.
Analysis of data across end-to-end applications.

Tools & Technologies:
Azure Synapse Analytics| Azure Data Factory (ADF).
Databricks (including Delta Lake and Unity Catalog)| SQL| PySpark |Python.
Hands-on data modelling tools (E.g., Erwin Data Modeler| ERStudio Data Architect| Power Designer etc.).
Experience with datawarehouse and Azure datalake.

Core Technical Competencies:
Strong understanding of data warehousing concepts and cloud architecture.
Design and implement conceptual| logical| and physical data models.
Develop scalable and efficient data architectures using Azure Synapse and Databricks.
Integrate data from diverse sources including ERPs| APIs| and cloud databases.
Work closely with data engineers| analysts| and business stakeholders to gather requirements.
Azure Synapse Analytics.