Principal Software Engineer, Salesforce, Data

Jobtailor; California (MO); On-site; USD 180,000 - 250,000; Full time

Job summary

Jobtailor is seeking a senior platform/engineer to lead the design and delivery of large‑scale Salesforce and data‑driven systems in the United States. You will own architecture across CRM, data pipelines, and AI accelerators, mentoring teams while driving technical strategy.

You will partner with product, data, and software engineers to build scalable solutions, ensure reliability, and shape long‑term roadmaps for enterprise customers.

Qualifications

• 12+ years in software/platform/data engineering or enterprise app development.
• Hands‑on Salesforce tech stack including Apex, Lightning, APIs, MuleSoft, Heroku.
• Experience building enterprise‑scale data platforms and pipelines.
• Strong Python, SQL, distributed data processing, and orchestration skills.
• Proven ability to design and operate large ETL/ELT pipelines (Airflow).

Responsibilities

• Define and drive technical strategy across Salesforce, Data 360, and AI initiatives.
• Architect and build large‑scale apps on Salesforce Core, API, and cloud services.
• Design data products, pipelines, and services for multiple domains.
• Lead scalable integrations between Salesforce, Data 360, Snowflake, and other systems.
• Develop AI‑powered accelerators and development tooling with Claude Code and Copilot.
• Collaborate with PMs, Architects, and engineers to shape platform roadmaps.
• Drive scalable data processing frameworks using Airflow and modern cloud architectures.
• Establish data quality, observability, governance, and reliability standards.
• Mentor senior engineers and lead multi‑team technical initiatives.
• Lead production investigations across apps, data pipelines, and services.

Skills

Salesforce Apex

Lightning Platform

Data engineering

Python

SQL

Airflow

ETL/ELT pipelines

APIs

MuleSoft

Cloud services

AI tooling

Leadership

Tools

Snowflake

GitHub Copilot

Claude Code

Cursor

Windsurf

Job description

Responsibilities

• Define and drive technical strategy across Salesforce CRM, Data 360, enterprise data platforms, and AI-enabled engineering initiatives.
• Architect and build large-scale applications using Salesforce Core, Apex, Lightning Platform, MuleSoft, Heroku, APIs, and cloud-native services.
• Design and implement enterprise data products, data pipelines, and data services supporting customer, account, marketing, and operational use cases.
• Build scalable integrations between Salesforce applications, Data 360, Snowflake, enterprise data warehouses, and external systems using APIs, streaming, and event‑driven architectures.
• Design and develop AI-powered engineering accelerators, developer tools, code generation frameworks, testing automation solutions, and operational tooling using Claude Code, Cursor, Windsurf, GitHub Copilot, and agentic AI technologies.
• Partner closely with Product Managers, Architects, Data Engineers, and Software Engineers to define platform roadmaps and long‑term architectural direction.
• Drive the design of highly scalable data processing frameworks leveraging Airflow, Python, SQL, streaming technologies, CDC patterns, and modern cloud‑native architectures.
• Establish engineering standards for data quality, observability, platform reliability, governance, and operational excellence.
• Mentor senior engineers and provide technical leadership across multiple teams and business domains.
• Lead complex production investigations spanning applications, integrations, data pipelines, and platform services.

Requirements

• 12+ years of experience across software engineering, platform engineering, data engineering, or enterprise application development.
• Strong hands‑on experience building applications on Salesforce technologies including Apex, Lightning Platform, CRM, APIs, MuleSoft, and Heroku.
• Strong experience building enterprise‑scale data platforms, data products, data pipelines, and data‑intensive applications.
• Deep expertise in Python, SQL, distributed data processing, orchestration frameworks, and modern data engineering practices.
• Experience designing and operating large‑scale ETL/ELT pipelines using Airflow or similar orchestration technologies.
• Proven experience integrating application platforms with enterprise data ecosystems using APIs, streaming technologies, event‑driven architectures, and cloud‑native services.
• Demonstrated experience building AI‑powered developer tools, engineering productivity platforms, or software delivery accelerators using modern AI platforms such as Claude Code, Cursor, Windsurf, GitHub Copilot, or equivalent technologies.
• Strong understanding of Generative AI, agentic workflows, MCP frameworks, and practical applications of AI within enterprise software engineering organizations.
• Ability to influence technical direction across multiple teams and organizations while remaining deeply hands‑on.
• Proven ability to take complex technical initiatives from concept through production deployment.