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# Lead Software Engineer

- **Company:** Franklin Templeton Investor Services, LLC
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $128,100.0 - $174,500.0
- **Contract:** Permanent contract
- **Skills:** Query Performance, Application Programming Interfaces (APIs), Artificial Intelligence, ARM Architecture, Microsoft Azure, Cloud Computing, Cluster Analysis, Code Review, Continuous Integration, Data Governance, Data Mart, Data Systems, Data Warehousing, Dimensional Modeling, Disaster Recovery, Python (Programming Language), Liquibase, Performance Tuning, Query Optimization, Role-Based Access Control, Cloud Services, Microsoft Copilot, Standard Sql, SQL Stored Procedures, SQL Databases, Systems Integration, GitHub Copilot, Snowflake, Gitlab, Deployment Automation, Data Management, Data Pipelines, Jenkins
- **Published:** October 8, 2026
- **Apply:** https://www.careerjet.com/job/use5c3ca262ddce505a825b7443d032c72/eaa

## About the Role

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

## Description

* 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