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Added 11 mins ago
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Franklin Templeton

Lead Software Engineer

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 5, 2026
Posting language: English
Posted: Oct 6, 2026

Original job description

At Franklin Templeton, we believe success is built through powerful partnerships. As a forward thinking asset manager, we build dynamic relationships with clients, understand their goals, and navigate complex markets together. We leverage cutting edge strategies and deep insights to unlock opportunities for long term wealth creation. Our talented, global teams bring expertise that is both broad and unique.

From our welcoming, inclusive, and supportive culture to our globally diverse business, we offer opportunities not only to help you reach your potential, but also to contribute to our clients’ success.

Lead Software Engineer

About The Department

Delivers reliable, SLA-driven data pipelines (holdings, transactions, positions)
Supports downstream analytics, reporting, and consumption systems in the Investments domain
Agile delivery: sprint-based planning, stand-ups, reviews
Cross-functional collaboration with architects, ingestion teams (ADF/APIs), and business stakeholders
Ownership-driven with aligned data/domain responsibilities
Culture of collaboration, continuous learning, and innovation
Focus on automation, new Snowflake capabilities, and AI-assisted development
Key impact: data accuracy, availability, performance, and cost efficiency

Job Overview

Lead implementation of architecture and translate platform strategy into scalable data solutions
Own end-to-end data pipeline strategy, reliability, performance, and cost optimization
Deliver scalable, enterprise-grade data solutions enabling business and analytics use cases
Drive platform roadmap / architectural direction

How You Will Add Value

Architect and design end-to-end data platforms: Source → Raw → Standard → Consumption
Own and enforce platform-level ELT frameworks and engineering standards (append-only, CDC, watermark, auditing)
Lead development of pipelines using Snowflake SQL, Stored Procedures, Tasks, Dynamic Tables
Design and govern ingestion patterns (API → ADF → Blob → Snowflake) ensuring resiliency and scalability
Drive advanced data modeling (dimensional models, SCD strategies, data marts)
Establish data quality, observability, monitoring, and alerting frameworks
Lead performance engineering and cost optimization (query tuning, clustering, pruning, warehouse usage)
Own warehouse strategy (sizing, concurrency, workload isolation)
Define and implement data governance standards (RBAC, masking, compliance, lineage)
Lead code reviews, engineering standards, and reusable frameworks
Mentor engineers and guide technical problem-solving across the team
Collaborate with architects, product owners, and business stakeholders
Translate enterprise architecture into implementable designs
Design and implement disaster recovery (DR) strategies and validate readiness through RTO/RPO testing

AI Fluency - AI-first mindset

Uses AI tools (Copilot, Cortex) to accelerate development and improve solution quality
Applies AI to optimize pipeline design, transformations, and performance
Validates AI outputs for correctness, efficiency, and architectural alignment
Identifies and implements AI-driven automation across development, testing, and operations
Drives adoption of AI-assisted development practices across the team

What Will Help You Be Successful In This Role

Deep hands-on experience with Snowflake, including:
Strong understanding of Snowflake architecture (storage, compute, cloud services)
Expertise in virtual warehouses, workload isolation, and concurrency management
Advanced query performance tuning and cost optimization
Experience with Stored Procedures, Tasks, Dynamic Tables, and orchestration patterns
Strong expertise in:
ELT architecture and frameworks (incremental, CDC, auditing, error handling)
Data warehousing and dimensional modeling (Facts, SCD Type 1/2, data marts)
Strong SQL and performance optimization skills
Python for orchestration and integrations
Proven experience designing and scaling production-grade data platforms
Familiarity with Medallion Architecture (Bronze/Silver/Gold)
Strong data governance (RBAC, masking, lineage)

Technical Environment

Core Stack: Snowflake (SQL, Stored Procedures, Tasks, Dynamic Tables), Python, ADF, APIs, Blob Storage
Operating Environment: Cloud-based (Azure + Snowflake ecosystem)
Workflow: Agile delivery, CI/CD (GitLab, Jenkins, Liquibase), standardized development and release practices
Quality & Reliability: Data quality, observability, monitoring, alerting, SLA adherence and incident management

Nice To Have Skills

Advanced clustering strategies and workload optimization
Experience with ADF, APIs, Blob storage
CI/CD frameworks and deployment automation
Exposure to Snowflake Cortex / AI capabilities and analytics use cases
GitHub Copilot and AI-driven engineering workflows

Work Schedule & Location

This role will work a hybrid schedule 3 days/week in any of our Franklin Templeton locations with a preference to locations in the Eastern time zone and Canada.

Franklin Templeton offers employees a competitive and valuable range of total rewards – monetary and non-monetary – designed to support their well-being and recognize their time, talents, and results. Along with base compensation, employees are eligible for an annual discretionary bonus, a 401(k) plan with a generous match, and recognition rewards. We also offer a comprehensive benefits package, which includes a range of competitive healthcare options, insurance, and disability benefits, employee stock investment program, learning resources, career development programs, reimbursement for certain education expenses, paid time off (vacation / holidays / sick / leave / parental & caregiving leave / bereavement / volunteering / floating holidays) and a motivational wellbeing program. We expect the annual salary for this position to range between $128,100 – $174,500, depending on location and level of relevant experience, plus discretionary bonus....

At Franklin Templeton, we believe your benefits should support your life, your goals, and your future. That’s why we offer a comprehensive Total Rewards package designed to help you thrive both personally and professionally.

Highlights Of Our Benefits Include

Paid Time Off: Three weeks of PTO in your first year
Health Coverage: Competitive medical, dental, and vision insurance to support your well-being
Retirement Savings: 401(k) plan with an 85% company match on pre-tax and/or Roth contributions, up to IRS limits
Equity & Investing: Employee Stock Investment Plan (ESIP) with discounted share purchase opportunities
Learning Education Assistance Program (LEAP): To support your ongoing growth and career advancement
Employee Investment Benefits: Opportunity to purchase company funds with no sales charge

Franklin Templeton is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.

Artificial intelligence or automated tools may be used to assist in the screening, assessment, or selection of applicants for this position.

Apply About employer

More about this job

Responsibilities

Lead the architecture, implementation, and operation of scalable Snowflake data platforms and end-to-end pipelines, ensuring reliability, performance, data quality, governance, and cost efficiency. Set engineering standards and platform direction, mentor engineers, guide disaster recovery readiness, and collaborate with architects, product owners, and business stakeholders.

Requirements

The role calls for deep hands-on Snowflake expertise, advanced SQL and performance tuning, and strong experience with ELT frameworks, data warehousing, dimensional modeling, and production-grade data platforms. Python, cloud-based Azure integrations, data governance, and familiarity with CI/CD and AI-assisted engineering are also relevant.

Skills

Snowflake
SQL
Python
Data Pipeline Architecture
ELT
Change Data Capture
Dimensional Modeling
Data Warehousing
Azure Data Factory
API Integration
Data Governance
Performance Optimization
Data Quality
Disaster Recovery
CI/CD
AI-Assisted Development

Benefits

Annual Discretionary Bonus
401(k) With Company Match
Recognition Rewards
Medical Insurance
Dental Insurance
Vision Insurance
Disability Benefits
Learning Resources
Career Development Programs
Education Expense Reimbursement
Paid Time Off
Wellbeing Program
Employee Investment Benefits

Visa sponsorship

Not detected in the job text

Keywords

Snowflake
SQL
Python
Azure
Azure Data Factory
Blob Storage
APIs
Stored Procedures
Tasks
Dynamic Tables
ELT
Change Data Capture
Data Warehousing
Dimensional Modeling
Medallion Architecture
Data Marts
Data Governance
Role-Based Access Control
Data Masking
Data Lineage
Data Quality
Observability
Performance Tuning
Cost Optimization
Disaster Recovery
Agile
CI/CD
GitLab
Jenkins
Liquibase

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