LMTS Platform Engineer - Data Cloud Platform

Salesforce, Inc.San Francisco, CA, United States

8 days ago

Job type

Full-time

Job 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.

Job CategorySoftware EngineeringJob Details

About Salesforce

Salesforce 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.We’re Salesforce, the Customer Company, inspiring the future of business with AI+ Data +CRM. We continue our own Digital Transformation to deliver customer success and accelerate growth. A key pillar of this transformation is building a strong data foundation to support internal, cross-Enterprise data needs through intelligent data sets-as-a-service, leveraging our own, best-in-class, Data Cloud platform for internal, go-to-market needs. We are seeking an experienced and committed Senior Software Engineer (LMTS) who will help deliver & support Salesforce’s Enterprise Data Foundations within Salesforce Data Cloud, as part of our Data Platform Services organization. This LMTS will work closely with product management, data science, data visualization, and analyst teams by building Data Cloud architecture, environments, and supporting robust data pipelines. This role requires embracing full accountability for technical deliveries through all phases of the development life cycle—from code to test to production, delivering high quality, secure, and resilient applications. The ideal candidate leverages a Platform Engineering mindset to design, build, and maintain foundational infrastructure and tools that standardize the development process and streamline efficiency. This role requires strong experience with data infrastructure, data architecture, ETL, SQL, automation, real-time data pipeline architecture, and data frameworks necessary to rapidly integrate disconnected and disparate data sources into automated datasets. The candidate must also possess a proven track record working with enterprise metrics and strong operational skills to drive speed, efficiency, and reliability. Responsibilities Salesforce Data Cloud Platform Engineering Collaborate with stakeholders to define and refine Enterprise data strategies, focusing on gathering, managing, and activating data across all major Operating Units and Lifecycle Data Domains. Design and develop platform Data Quality, Governance, Lifecycle processes, in alignment with control teams & service providers in our larger organization. Ensure all application code adheres to secure coding practices and internal BT standards. Develop & enact feature certification frameworks, acting as subject matter expert for data, pipeline design, and other Data Cloud features, and as enablement lead for our direct customers, and enterprise at large. Lead efforts in identifying and implementing automation to improve efficiency and reduce manual efforts, embodying platform engineering principles. Ensure all configuration changes are treated as code (Configuration as Code), checked into source control, and deployed in an automated and fully tested manner Build and own automation and monitoring frameworks to showcase reliable, accurate, and easy-to-understand metrics and operational KPIs for data pipeline quality and performance. Design and develop robust, highly scalable, and resilient Continuous Delivery systems. Create and drive comprehensive automated test strategies and plans for Data Cloud projects and technical solutions, including unit tests, integration tests, functional tests, acceptance tests, performance tests, and security scans to ensure quality, performance, and reliability. Automate and extend internal logging, monitoring, CI / CD, and incident management. Proactively identify and resolve reliability and data quality problems. Monitor, troubleshoot, and optimize Salesforce Data Cloud environments for performance, reliability, and scalability. Capture & catalog Service Level Indicators (SLIs), define and manage Service Level Objectives (SLOs) and Service Level Agreements (SLAs) for data platform reliability and performance. Act as the primary point of contact for major escalations related to platform reliability. Support the launch and operational support of multiple Salesforce Orgs and Data Cloud tenants, including dependent features. Participate in developing and executing disaster recovery plans with continuous monitoring and alerting. Ensure seamless integration of Salesforce Data Cloud with other Salesforce products and third-party applications. Support boundary Enterprise data platforms, including ingress / egress / zero-copy data connections with Amazon Web Services, Snowflake, out-of-box Connectors, and supported API endpoints. Foster strong collaboration among globally distributed team members, leading by example in delivering high-quality features and providing technical leadership and guidance Align in-Platform workstreams with larger Operational Excellence and Developer Excellence teams. Minimum Qualifications 8+ years of relevant industry experience in platform-specific development, implementation, or support in an enterprise IT environment, emphasizing data engineering, monitoring, alerting, and visualization systems. A related technical degree (Bachelor's or equivalent professional experience) is required. Deep knowledge of object-oriented programming and other scripting languages, such as Java, Python, Scala, C#, Go, Node.JS, C++, C, or Shell. Strong SQL skills and experience with relational and non-relational databases (e.g., Postgress / Trino / Redshift / Mongo / Snowflake). Proficiency in SOQL / SAQL and data modeling for analytics. Proven experience designing and developing distributed systems at scale. In depth experience of design patterns, data structures, algorithms, and concurrency. Deep knowledge of cloud infrastructures (AWS, Azure, GCP). Advanced expertise with observability and incident management tools such as Datadog, Splunk, Grafana, Tableau, New Relic, and PagerDuty. Experience managing reliability and performance within the Salesforce ecosystem. Proven ability in incident escalation and disaster recovery management. Experience using telemetry and metrics to drive operational excellence in Continuous Delivery pipelines. Experience with Agile development methodology and SCRUM / AGILE. Strong relationship-building skills across technical and business teams. Excellent verbal, written, and interpersonal communication skills. Salesforce Certified Platform Developer I certification (or ability to achieve within 6 months). Preferred Qualifications Experience in Enterprise-scale environments, particularly with Salesforce Data Cloud (CDP), Heroku, and our Core Salesforce Platform. Experience with configuration management tools (Ansible, Puppet, Chef) and log management (Elastic, Logstash, Kibana). Experience with Continuous Delivery platforms and adopting Infrastructure as Code (IaC) principles, utilizing tools such as Kubernetes, Docker, Terraform, Jenkins, Git, Spinnaker, or Gearset Deep hands-on experience in complex event-driven architectures and stream processing in a variety of technologies. Hands-on experience with Streaming technologies like Kafka. Understanding of data governance practices such as metadata management, data lineage, and data glossaries. Experience with Big-Data / ML and S3. Familiarity with Salesforce development technology stack like Flows and Apex. Relevant industry certifications, including Salesforce Data Cloud Consultant / Architect, Salesforce Marketing Cloud Consultant, or Salesforce Certified Platform Developer II, and Salesforce Certified JavaScript Developer

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Cloud Platform Engineer • San Francisco, CA, United States

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