Senior Software Engineer

Location: New York

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.

Job Overview Design, build, and optimize Snowflake-based data platforms and ELT pipelines

Own pipeline reliability, performance, and cost optimization

Deliver scalable, high-quality data for analytics and business decision-making

Ensure SLAs and reliability for production pipelines

Implement solutions aligned to defined architecture and engineering standards

How you will add value

Design and build end-to-end data pipelines:
Source Raw Standard Consumption Implement robust incremental frameworks (append-only, CDC, watermark-based)
Develop ELT pipelines using Snowflake SQL, Stored Procedures, Tasks, and orchestration patterns

Design and manage ingestion pipelines (API ADF Blob Snowflake), handling real-world challenges (pagination, retries, schema changes)
Build and optimize complex transformations within Snowflake Design and maintain dimensional models (fact tables, SCD Type 1/2)
Implement data quality, monitoring, logging, and alerting mechanisms

Drive query performance tuning (Query Profile, clustering, pruning)
Optimize warehouse usage, concurrency, and cost efficiency

Implement RBAC, masking, and governance standards

Lead code reviews, best practices, and reusable frameworks

Collaborate with architects, analysts, and business stakeholders to translate requirements into solutions

Ensure SLA adherence for production pipelines AI Fluency - AI-first mindset

Uses AI tools (Copilot, Cortex) to accelerate development, troubleshoot pipelines, and improve code quality

Uses AI to assist in designing pipelines, transformations, and improving existing solutions

Reviews and refines AI-generated outputs to ensure accuracy, efficiency, and alignment with data models and standards

Identifies where AI can help reduce manual effort (testing, documentation, repetitive tasks)
Uses AI to learn new Snowflake features and improve development practices

Uses AI to improve personal development productivity and solution quality

Technical Environment Core Stack:
Snowflake (SQL, Stored Procedures, Tasks), Python, Azure Data Factory (ADF), APIs, Blob Storage Operating Environment:
Cloud-based (Azure + Snowflake ecosystem)
Workflow:
Agile delivery, CI/CD (Git Lab, Jenkins, Liquibase), ticketing via standard tools (e.g., Jira)
Quality & Reliability:
Data quality, monitoring, observability, alerting, incident handling

What will help you be successful in this role Strong hands-on experience with Snowflake, including:

Solid understanding of Snowflake architecture (storage, compute, cloud services)
Virtual warehouses, workload isolation, and concurrency handling

Strong query performance tuning and cost optimization

Stored Procedures, Tasks, and orchestration patterns

Exposure to or experience with Dynamic Tables Strong expertise in:

ELT frameworks (incremental processing, CDC, auditing, error handling)
Data warehousing and dimensional modeling (Facts, SCD Type 1/2)
Strong SQL and query optimization skills

Python for orchestration and integrations

Experience building and operating production-grade data pipelines

Familiarity with Medallion Architecture (Bronze/Silver/Gold)
Nice to have skills

Advanced clustering and performance optimization

Data governance…