Data Engineer - MTS/SMTS/LMTS

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 Category Software Engineering Job 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. Ready 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. About The Role We are seeking a highly skilled and motivated Data Engineer to join our Growth & Retention Intelligence team. In this role, you will design, build, and scale the data that power our machine learning ecosystem – enabling consistent, reliable, and real-time access to features across development, training, and production environments. You’ll collaborate closely with data scientists, ML engineers, and data platform teams to streamline feature engineering workflows and ensure seamless integration between offline and online data sources. You’ll be expected to work across multiple domains including data architecture, distributed systems, software engineering, and MLOps. You will help define and implement best practices for feature registration, drift, governance, lineage tracking, and versioning, all while contributing to the CI/CD automation that supports feature deployment across environments. What You’ll Do Key Responsibilities Feature Store Development: Implement and maintain scalable features serving offline (batch), online (real-time), and streaming ML use cases. Streaming & Real-Time Data Processing: Design and manage streaming pipelines using technologies like Kafka, Kinesis, or Flink to enable low-latency feature generation and real-time inference. Feature Governance & Lineage: Define and enforce governance standards for feature registration, metadata management, lineage tracking, and versioning to ensure data consistency and reusability. Collaboration with ML Teams: Partner with data scientists and ML engineers to streamline feature discovery, definition, and deployment workflows, ensuring reproducibility and efficient model experimentation. Data Pipeline Engineering: Build and optimize ingestion and transformation pipelines that handle large-scale data while maintaining accuracy, reliability, and freshness. CI/CD Automation: Implement CI/CD workflows and infrastructure-as-code to automate feature store provisioning and feature promotion across environments (Dev → QA → Prod). Monitoring & Observability: Develop monitoring and alerting frameworks to track feature data quality, latency, and freshness across offline, online, and streaming systems. What We’re Looking For Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field. 5+ years of experience in data engineering roles. Strong proficiency in Python and familiarity with distributed data frameworks such as Airflow, Spark or Flink. Hands‑on experience with feature store technologies (e.g., Feast, SageMaker Feature Store, Tecton, Databricks Feature Store, or custom implementations). Experience with cloud data warehouse (e.g., snowflake) and transformation framework (e.g. dbt) for data modeling, transformation and feature computation in batch environment. Expertise in streaming data platforms (e.g., Kafka, Kinesis, Flink) and real-time data processing architectures. Experience with cloud environments (AWS preferred) and infrastructure‑as‑code tools (Terraform, CloudFormation). Strong understanding of CI/CD automation, containerization (Docker, Kubernetes), and API‑driven integration patterns. Knowledge of data governance, lineage tracking, and feature lifecycle management best practices. Experience with unstructured databases (vector or graph databases) and RAG pipelines. Excellent communication skills, a collaborative mindset, and a strong sense of ownership. Preferred Qualifications (Bonus Points) Experience with Salesforce Ecosystem Experience with context engineering including structuring data, prompts, and logic for AI systems, managing memory and external knowledge, etc Unleash Your Potential When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do 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. Accommodations If you need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form. Please 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. Posting Statement Salesforce 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. In 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: At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $117,200 - $260,100 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable. #J-18808-Ljbffr Salesforce