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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Salesforce Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $99,400.0 - $150,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Cloud Computing, Information Engineering, Data Infrastructure, Cursor (Graphical User Interface Elements), Database Development, Github, Graph Database, Python (Programming Language), Software Tools, Salesforce.Com, SQL Databases, Oracle Hyperion, Informatica Powercenter, Snowflake, Coupa Procurement, Data Pipelines, Workday - **Published:** September 12, 2026 - **Apply:** https://www.jobmonkeyjobs.com/career/28013658/Data-Engineer-Washington-Seattle-7447 ## About the Role 5-7 years of hands-on experience in data engineering or analytics - Proficiency in SQL (test will be administered) - Experience with Python, dbt Cloud, and dbt Core, Airflow and Snowflake - Experience with CI/CD pipelines and GitHub - Curiosity and passion for data and emerging technologies, including AI/ML tooling - Strong communication skills and ability to work cross-functionally Preferred Qualifications: - dbt Certification - Familiarity with financial data sources (Workday, Coupa, Concur, Hyperion, SalesForce) - Experience building or supporting Tableau dashboards - Exposure to AI-assisted development tools (e.g., Claude, Cursor, Snowflake CoCo) - Familiarity with semantic layer concepts and knowledge graphs - Experience creating enablement materials or conducting technical training sessions - Natural problem solver who thrives in ambiguous environments and brings a structured, solutions-oriented mindset to every challenge ## Description We are seeking a Data Engineer to join the Finance Data Office team at Salesforce. This role supports Finance functions including Finance & Strategy, Revenue Operations, and others, contributing to data pipelines that power daily operational reporting, monthly close processes, and quarterly earnings reporting. The ideal candidate has foundational SQL and data engineering skills with hands-on experience in Snowflake, Airflow, and dbt, and a desire to grow in a business-oriented data environment. You'll work closely with senior engineers and business partners to build, maintain, and improve key datasets. Responsibilities: - Support the maintenance and development of data pipelines in Snowflake, Airflow and dbt Cloud - Assist in migrating legacy data processes to modern data engineering tools (dbt, Python, Airflow, Informatica) - Help land and wrangle datasets from sources including Salesforce, Coupa, Workday, and Concur - Conduct testing and auditing of ELT pipelines to improve accuracy and efficiency - Translate business requests into documented data requirements - Collaborate with stakeholders to define KPIs and validate data results - Conduct proof of concept evaluations of emerging AI and data platform tools to assess feasibility and business value - Partner with Finance data teams to enable adoption of new tools and technologies through training, documentation, and hands-on support - Establish and promote best practices for tool usage, data development standards, and data platform governance across the Finance data organization ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Destigmatizing the Workplace: Building Real Inclusion](https://www.wearedevelopers.com/videos/1492-destigmatizing-the-workplace-building-real-inclusion) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [WeAreDevelopers LIVE - How DevRel Makes Tech More Human](https://www.wearedevelopers.com/videos/2149-wearedevelopers-live-how-devrel-makes-tech-more-human) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Turn Community Events Into a Powerful AI GTM Engine: The Daytona Playbook](https://www.wearedevelopers.com/magazine/732-how-to-turn-community-events-into-a-powerful-ai-gtm-engine-the-daytona-playbook) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence)