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fast food restaurant manager
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Iris Software Inc.

Data Architect (AWS)

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 5, 2026
Experience: 8+ years hands-on data engineering experience, including production ownership
Posting language: English
Posted: Oct 6, 2026

Original job description

Iris's direct client, one of the Top 5 Bank in Canada, is looking to hire a Data Architect (AWS) a long-term opportunity at Toronto, ON (Hybrid).

Our client is a Canadian multinational financial services company and the largest bank in Canada by market capitalization. The bank serves over 17 million clients and has more than 89,000 employees worldwide. Bank is serving individual consumers, small and middle market businesses and large corporations with a full range of banking, investing, asset management and other financial and risk-management products and services.

Position: Data Architect (AWS)

Location: Toronto, ON (Hybrid)

Duration: 12+ Months

Required Skills

Client & Relationship Ownership

Act as the primary onsite technical point of contact for all engineering/architecture matters related to the risk and regulatory data platform
Build and sustain trusted advisor relationships with client stakeholders (risk technology, compliance, data platform, and business teams)
Represent the delivery organization in client forums, steering committees, and technical design reviews
Proactively surface risks, dependencies, and modernization opportunities to the client

Delivery Ownership

Own and manage offshore delivery team output - assign work, review deliverables, enforce engineering standards, and ensure on-time, high-quality delivery
Bridge onsite/offshore communication gaps; translate client requirements into actionable offshore work plans
Own technical quality gates: code reviews, architecture reviews, data validation/reconciliation sign-off

Technical/Architecture

Design and validate migration patterns from legacy Netezza/SSIS ETL to AWS-native pipelines (Glue, PySpark, S3, Redshift, Lambda etc.)
Provide hands-on architecture and coding guidance - this is a working architect role, not purely advisory
Own data migration reconciliation strategy (source-to-target validation, PII/sensitive data handling, encryption)
Design for regulatory reporting requirements (auditability, lineage, data quality controls) typical of retail/wholesale enterprise risk platforms
Optimize Redshift schema/performance and Glue/PySpark job design for regulatory batch and reporting workloads
Support integration with downstream risk model consumption patterns (e.g., model inference pipelines, scoring APIs)

Required Technical Skills

8+ years hands-on data engineering experience, including production ownership
Deep expertise in legacy ETL platforms: Netezza (SQL, nz unload alternatives, performance tuning), SSIS
Strong hands-on AWS Lakehouse skills: S3, Redshift, Glue, PySpark, Lambda etc.
Proven experience designing and executing large-scale data migrations (legacy MPP → cloud lakehouse / warehouse)
Strong SQL and data modeling skills (dimensional and normalized models)
Experience with data quality, reconciliation, and validation frameworks for regulated data
Familiarity with encryption/PII handling and data governance controls
Understanding of CI/CD and orchestration tooling (Airflow, Glue workflows, or equivalent)

Preferred/Plus

Banking domain experience, specifically enterprise risk (retail and/or wholesale) and regulatory compliance/reporting
Familiarity with risk model ecosystems (e.g., credit risk scoring, AIM/ARM-type models, SageMaker-based inference)
Experience with Microsoft Fabric or similar competing platforms (useful for informed architecture debates)
AWS certification (Solutions Architect or Data Analytics Specialty)

Required People/Leadership Skills

Executive presence - comfortable presenting to senior client technical and business stakeholders
Strong stakeholder management: able to earn trust incrementally and defend design decisions under scrutiny
Team leadership: able to direct and mentor an offshore delivery team without daily hand-holding from presales/account leadership
Excellent written and verbal communication - able to translate deep technical detail into business-relevant narrative
Comfortable operating with ambiguity in an early-relationship, trust-building phase
Ownership mindset - treats the account as their own, not just an assigned task

Success Criteria (First 6 Months)

Established as the client's trusted technical go-to for the risk/regulatory platform
Offshore delivery operating smoothly under this person's direction with minimal escalations
Migration architecture validated and accepted by client architecture/governance bodies
Measurable progress on legacy-to-Lakehouse migration milestones

Thanks and Regards,

Raghav Ranjan

Iris Software / SSA Infosystems Inc

Royal Bank Plaza – North Tower

200 Bay Str. Toronto, ON, M5J 2J2

Email: raghav.ranjan@irissoftware.com

www.irissoftware.com

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More about this job

Responsibilities

Lead the technical relationship and architecture for the client's risk and regulatory data platform, including migration from legacy Netezza and SSIS systems to AWS-native data pipelines. Direct offshore delivery, ensure engineering quality and regulatory controls, and guide migration validation, performance, and downstream risk-model integrations.

Requirements

Requires 8+ years of hands-on data engineering experience, strong expertise in Netezza, SSIS, AWS lakehouse services, SQL, data modeling, and large-scale cloud migrations. Candidates should also demonstrate regulated-data quality and governance experience, leadership of offshore teams, and strong client-facing communication; banking risk experience and AWS certification are preferred.

Skills

AWS
Data Architecture
Data Engineering
Netezza
SSIS
Amazon S3
Amazon Redshift
AWS Glue
PySpark
AWS Lambda
SQL
Data Modeling
Data Migration
Data Reconciliation
Data Governance
Offshore Team Leadership

Visa sponsorship

Not detected in the job text

Hiring contact

Raghav Ranjan

Hiring contact email

raghav.ranjan@irissoftware.com

Keywords

AWS
Amazon S3
Amazon Redshift
AWS Glue
PySpark
AWS Lambda
Netezza
SSIS
SQL
Airflow
Data Architecture
Data Engineering
Data Migration
Lakehouse
Data Warehouse
Data Modeling
Dimensional Modeling
Data Quality
Data Reconciliation
Data Validation
Data Lineage
PII Handling
Encryption
Data Governance
CI/CD
Regulatory Reporting
Enterprise Risk
Credit Risk Scoring
Amazon SageMaker

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