Software Engineering PMTS - Data Engineer
Salesforce is hiring a Software Engineering PMTS - Data Engineer for a remote role open to applicants in Poland. Level rates it ; you can apply on Salesforce.
Level's read on this job
- Works on AI ●●●○ is how Level rates this data engineer role: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions AI agents among its tools and skills.
- Salesforce has 1,500+ other open roles on Level.
- Posted in the last few days.
AI in this role
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 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.
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 Team:
Digital Enterprise Technology (DET) at Salesforce builds the internal engines that power our business. The Machine Learning & Innovation (MLI) team is the applied science and infrastructure strike-force responsible for "Foundry," our unified ML/AI Platform. We operate as "Customer Zero," building the high-velocity, real-time streaming feature platforms and recommendation models that power internal products like the Events App and enterprise-wide personalization.
Role Overview:
As a Senior Staff Data Engineer, you will own the foundational data lake infrastructure that supplies all downstream machine learning models. You will build and maintain the massive, highly reliable data pipelines required to transform raw enterprise data into point-in-time correct training datasets and offline features, ensuring the lifeblood of our AI platform flows without interruption.
What You'll Do:
- Manage and optimize the foundational data lake infrastructure, specifically focusing on Apache Iceberg table maintenance, compaction, and vacuuming.
- Architect and maintain complex Snowflake-to-lake Airflow DAGs for massive-scale data transformations.
- Design and implement robust data transformation pipelines, enforcing rigorous event schemas and time-partition column standards (e.g., ts/ds).
- Integrate offline data stores with the Zipline feature platform to support automated historical backfills and point-in-time correct training data generation.
- Troubleshoot and resolve complex data quality anomalies, pipeline failures, and performance bottlenecks in distributed data systems.
- Establish Data-as-a-Product practices, defining clear data contracts, SLAs, and data lineage tracking mechanisms.
What You Bring:
- 15+ years of experience in data engineering, data architecture, and distributed data processing.
- Deep expertise in modern data lake architectures (Apache Iceberg, Delta Lake) and data warehousing (Snowflake).
- Advanced proficiency in distributed compute engines (Apache Spark, EMR) and workflow orchestration (Apache Airflow).
- Expert-level SQL optimization skills and strong programming experience in Python or Scala.
- Experience integrating offline data platforms with machine learning feature stores (Zipline, Feast).
- A meticulous approach to data quality, schema enforcement, and pipeline reliability.
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.
How we rate this
Software Engineering PMTS - Data Engineer at Salesforce rates 67 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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