Staff Data Engineer
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.
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 mostly remote, but periodic international travel within Latam or to the US will be required.
What you’ll do
Architect Scalable Data Platforms: Design systems supporting analytics, ML/AI products, reporting, APIs, integrations, and customer-facing data products.
Own the Data Architecture and Lifecycle: Design how data is modeled, stored, partitioned, transformed, validated, and served - not just how it moves between systems.
Build Reliable Pipelines: Architect scalable, observable, replayable, and cost-efficient batch, incremental, and near-real-time pipelines.
Design Data Models and Storage Patterns: Define schemas, partitioning and clustering strategies, access patterns, and storage layouts optimized for scale, performance, and cost.
Productionize ML and AI Products: Partner with Data Science to turn models and experimental outputs into reliable production capabilities.
Define Data Standards: Establish best practices for data contracts, modeling, testing, observability, and production readiness.
Create Trusted Data Products: Build governed datasets and serving patterns for dashboards, APIs, integrations, ML workflows, and agent-ready use cases.
Shape Platform Strategy: Influence decisions around storage, processing frameworks, serving patterns, governance, scalability, and cost.
What we’re looking for
Senior Technical Experience: 8+ years in data engineering, data platform engineering, or similar roles in data-intensive environments.
Data Architecture and Modeling Depth: Deep experience designing data models and storage architectures for large-scale systems, including schema design, partitioning and clustering, data layout, access patterns, and distributed processing.
Modern Data Platform Expertise: Strong hands-on experience with modern warehouse, lakehouse, or distributed data platforms. Experience with Databricks and Snowflake is helpful, but we care more about understanding the underlying architecture and tradeoffs around storage, compute, scalability, performance, reliability, and cost.
Strong Engineering Foundations: Production-grade SQL and strong programming skills in Python, Scala, Java, or similar languages.
Batch and Streaming Architecture: Experience designing batch, incremental, and near-real-time systems at scale, including replay, backfill, and failure recovery.
Systems Thinking: Ability to design data systems from requirements and first principles rather than starting with a preferred technology or framework.
End-to-End Ownership: Experience designing how data is structured, stored, transformed, validated, and served - not just building ingestion or ETL pipelines.
ML/AI Product Experience: Experience supporting production ML or AI systems, ideally including LLMs, VLMs, embeddings, or multimodal data products.
Data Quality and Observability: Experience with validation, monitoring, lineage, alerting, and incident response for critical data systems.
Pragmatic Technical Leadership: Strong judgment around architectural tradeoffs, platform design, and balancing long-term solutions with practical delivery.
Direct Communication: Ability to clearly explain architecture, risks, and tradeoffs across technical and non-technical audiences.
English Fluency: B2+ written and spoken English required.
Ownership: You own outcomes, not just pipelines.
Please be aware that Vidmob will only contact candidates through emails ending in @vidmob.com. We will never ask for personal information, such as your Social Security number, bank account number, or password, through email. If you receive an email claiming to be from Vidmob that does not come from a @vidmob.com email address, or if the email asks for personal information, please do not respond and report the email to us at [email protected]