Staff Data Engineer
Vidmob
| Company | Vidmob |
| Category | Engineering |
| Location | São Paulo |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 22 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (ashby) |
Description
Vidmob is the creative data company. Its scoring software and analytics have become an essential ingredient in the creative and media decisions of the world’s largest marketers and agencies, as they strive to drive business results through improved creative effectiveness. As the leader in creative data, Vidmob’s influence lies in its partnerships and integrations across the digital ad ecosystem, its dozens of proprietary models, and in operating the industry’s most robustly instrumented human-reinforcement learning model for creativity.
We are seeking an experienced Staff Data Engineer to architect, scale, and operationalize the data systems that power Vidmob’s creative intelligence platform.
Vidmob turns creative into a measurable growth driver by connecting creative assets, model outputs, platform metadata, media delivery, and business outcomes. That requires scalable, reliable data platforms for analytics, machine learning, customer-facing reporting, APIs, partner integrations, and AI-driven workflows.
This role is especially important as Vidmob builds more products driven by ML and AI, including LLMs, VLMs, creative scoring systems, and agentic workflows. We need a data engineering leader who can partner deeply with Data Science to productionize models, serve model outputs reliably, and turn experimental intelligence into durable customer-facing products.
Because AI is changing how data systems are built and consumed, you need to be an AI-forward practitioner. You will use AI to accelerate engineering, validation, observability, root-cause analysis, documentation, and data discovery.
Our global team works in English, so strong written and spoken English skills are essential. This position is most remote, but periodic international travel within Latam or to the US will be required.
WHAT YOU’LL DO
- Architect Scalable Data Platforms: Lead the design and development of data systems that support analytics, ML/AI products, reporting, APIs, integrations, and customer-facing data products.
- Own the Data Lifecycle: Drive ingestion, transformation, modeling, validation, lineage, publishing, and serving across Vidmob’s creative, media, customer, model-output, and performance data.
- Build Reliable Pipelines: Architect batch and near-real-time pipelines that are scalable, observable, replayable, and cost-efficient.
- Productionize ML and AI Products: Partner with Data Science to turn models, scores, embeddings, prompts, evaluations, and experimental outputs into reliable production data products and customer-facing capabilities.
- Support LLM and VLM Workflows: Build data foundations for AI-powered products using LLMs, VLMs, multimodal analysis, agent workflows, and reinforcement learning.
- Define and Enforce Data Standards: Establish best practices for data contracts, pipeline design, testing, reviews, observability, and production readiness.
- Create Trusted Data Products: Build governed datasets and serving patterns that support dashboards, APIs, exports, partner integrations, ML workflows, benchmarks, and agent-ready use cases.
- Support Platform and Partner Integrations: Build reliable data flows with ad platforms, DSPs, measurement partners, creative systems, customer environments, and internal product surfaces.
- Shape Platform Strategy: Influence long-term decisions around tooling, storage, processing frameworks, serving patterns, governance, and cost structure.
WHAT WE’RE LOOKING FOR
- Senior Technical Experience: 8+ years in data engineering, data platform engineering, or analytics engineering in SaaS, platform, AdTech, MarTech, marketplace, or other data-heavy environments.
- Modern Data Platform Expertise: Deep experience with modern warehouse, lakehouse, orchestration, and transformation technologies including Snowflake, Databricks, and BigQuery, as well as relational and noSQL databases.
- Strong Engineering Foundations: Production-grade SQL and strong programming
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