
Data Engineer
Role summary
Salesforce is seeking a Full-Stack Data Engineer to build and scale the product data platform powering its next era of agentic intelligence. This role involves designing and implementing near real-time and batch telemetry pipelines, semantic layers, and programmatic discovery systems using technologies like Spark, Trino, Flink, Kafka, and DBT. The engineer will apply software engineering best practices, including CI/CD and observability, and contribute to a trusted data foundation for analytics, ML models, and autonomous agents. Experience with cloud infrastructure (AWS) and AI data engineering patterns is highly valued. This is a hybrid role based in Mexico City.
## Description
DATA ENGINEER
Mexico City
About the Role
We’re building the product data platform that will power Salesforce’s next era of agentic intelligence — delivering smarter, adaptive, and self-optimizing product experiences.
As a Full-Stack Data Engineer, you’ll design and build scalable systems that process hundreds of thousands of context-rich product signals. These signals fuel analytics, customer-facing products, ML models, and autonomous agents.
You’ll work on:
- Near real-time and batch telemetry pipelines for trusted signal capture
- Semantic layers and data products for reusable insights
- Programmatic discovery via metadata, MCP, and knowledge graphs
This isn’t a typical data engineering role. We’re looking for creative, systems-minded engineers working outside of the “data engineer” box, fluent in both data and AI, and excited to navigate ambiguity, cross boundaries, and drive real impact.
What You’ll Do
- Build and scale fault tolerant batch and streaming data pipelines using Spark, Trino, Flink, Kafka, DBT
- Design programmatic consumption layers to make product signals easy to define, discover, and reuse
- Apply software engineering best practices to data systems: testing, CI/CD, observability
- Evolve systems to support not just human analysis, but autonomous agent reasoning
- Contribute to a trusted data foundation powering decisions, AI agents, and adaptive products
- Collaborate across orgs with telemetry engineers, product leaders, data scientists, and AI builders
What We’re Looking For
- Strong experience in data engineering, with strong software engineering fundamentals
- Expertise with big data frameworks: Spark, Trino/Presto, DBT, Snowflake
- Experience with streaming systems like Flink and Kafka, incl. distribution strategy (topics & partitions)
- Solid understanding of semantic layers, data modeling, and metrics systems
- Experience with cloud infrastructure, particularly AWS (e.g., S3, EMR, ECS, IAM), Containerization
- Bonus: fluency in AI data engineering patterns and tools like MCP
- Bonus: experience with knowledge graphs and modern metadata systems
- Strong communicator and collaborator — comfortable working across teams and domains
- Curious, pragmatic, and impact-driven mindset
Why Join Us
Help shape how Salesforce leads the digital labor revolution. You’ll be at the heart of transforming raw product signals into intelligent decisions — for everyone from engineers to sales reps to AI agents. If you’re excited to design resilient, trusted, and intelligent systems at scale, we’d love to hear from you.
Sample Informatica interview questions
- 1
What are the key components and considerations in designing a low-latency cloud monitoring system?
system designmedium - 2
Decode Ways Determine the number of valid ways to decode a string of digits. Input: s = "10" Output: 1 Explanation: The string can only be decoded one single way, as the sequence '10' maps exclusively to the letter 'J'.
codingmedium - 3
Find the majority element in an array. Given an array of size n, find the majority element. The majority element is the element that appears more than ⌊n / 2⌋ times. You may assume that the majority element always exists in the array. Input: nums = [3, 2, 3] Output: 3 Explanation: The number 3 appears 2 times, which is strictly greater than n/2 (1.5).
codingmedium
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