{"id":2975047,"url":"https://alion.io/job/salesforce-staff-senior-staff-data-platform-engineer-slack","title":"Staff & Senior Staff Data Platform Engineer - Slack","company":{"id":70,"name":"Salesforce","domain":"salesforce.com","url":"https://alion.io/company/salesforce","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"A","score":88,"open_postings":448,"ghost_share":0.013,"stale_share":0.598,"repost_share":0.06,"time_to_fill_p50_days":21,"computed_at":"2026-10-21T05:46:15Z"}},"role":"Data Science","role_family":"Data Science","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","New York, United States","Atlanta, United States","Washington, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":197300,"max":365200,"currency":"USD","period":"year","gross":null,"usd_annual":365200},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agentforce","optional":false},{"name":"AI Agents","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Python","optional":false},{"name":"Slack","optional":false},{"name":"Amazon S3","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Databricks","optional":true},{"name":"dbt","optional":true},{"name":"Scala","optional":true},{"name":"Snowflake","optional":true},{"name":"Spark","optional":true},{"name":"SQL","optional":true},{"name":"Superset","optional":true},{"name":"Terraform","optional":true},{"name":"Trino","optional":true},{"name":"TypeScript","optional":true}],"status":"live","first_seen_at":"2026-10-20T00:00:00Z","employer_posted_date":"2026-10-20","last_verified_at":"2026-10-21T12:51:20Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.\nJob Category\nSoftware EngineeringJob Details\nAbout Salesforce\nSalesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword - it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.\nReady to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce.\nAgents are changing how people build software and analyze data. Slack’s data platform needs to support both agents that surface insights, and developer tools that use data to provide quantitative feedback in the product iteration process.\nWe’re looking for a Staff or Senior Staff engineer to help build out Agentic Analytics at Slack. You’ll collaborate on technical direction, build, and go from early prototypes through production. Your work could span many parts of the data stack: ingestion, infrastructure, semantic layers, and the interfaces that make data useful to humans and AI agents.\nYou’ll partner with engineers across Data Engineering, Data Science, product, core infrastructure, and developer experience to quickly iterate on high leverage problem spaces and ship pragmatic solutions.\nYou’ll help us:\nBuild data platform for agents. Design APIs, MCPs, and tools that let agents map data concepts to the right entities in the data warehouse.\nMake data digestible. Improve our semantic layer so people and agents alike can navigate metric definitions, lineage, ownership, and reliability.\nMake data on time (or provide signal when it’s not). Build ingestion and infrastructure for timely analytics, and experimentation. Evaluate tradeoffs between freshness, accuracy, reliability, and cost.\nShip tools that make data easy to analyze. Make it easy to draft accurate queries, do root cause analysis, and build visualizations.\nOwn the path to production. Drive architecture, implementation, rollout, and adoption.\nRaise the engineering bar across teams by helping engineers make good design decisions, resolve technical dependencies, and grow through mentorship and leading by example.\nHow you work matters:\nYou’re a high velocity engineer. You decompose problem spaces into digestible chunks and constantly iterate.\nYou’re biased toward action. You love to prototype to test ideas and get feedback early, but are okay throwing away bad ideas.\nYou can quickly build context in unfamiliar areas. You can move between a pipeline, a service, or a developer tool, build enough context to contribute. You also know when to ask for help when it speeds things up.\nYou balance speed and judgment. You can get a prototype off the ground quickly, but also build a reliable and scalable production system\nMinimum qualifications:\n8+ years of experience building and operating a data platform\nA track record of leading complex technical projects across teams as an individual contributor\nStrong software engineering skills balanced with deep data expertise\nClear technical communication and the ability to build alignment with engineers, data scientists, analysts, and product partners\nStrong proficiency in programming languages like Python, Go, Java, or similar\nBonus points for:\nExperience building infrastructure or tools for AI agents\nExperience with semantic layers, metrics platforms, data catalogs, or lineage. These might include familiarity with tools like Airflow, dbt, Databricks, sqlmesh, Datahub, Superset or Snowflake\nExpertise in SQL & Python to build data pipelines\nExperience building APIs, SDKs, or self-service platforms that other engineers use.\nPractical experience using AI development tools to accelerate implementation while maintaining engineering quality.\nTechnologies We Use:\nData: Trino, Spark, Pinot, Hive, Airflow, Iceberg, Spark, Datahub, Kafka\nStorage: S3\nInfrastructure: Terraform, AWS\nLanguages: Python, Go, SQL, Scala, Typescript\nUnleash Your Potential\nWhen you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance andbe your best, and our AI agents accelerate your impact so you cando your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what’s possible - for yourself, for AI, and the world.\nAccommodations\nIf you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form.\nPlease note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our Candidate Privacy Statement for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.\nPosting Statement\nSalesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.\nIn the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions.\n\nThe typical base salary range for this position is $197,300 - $365,200 annually. 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