Staff Data Engineer

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Vidmob

WebsiteLinkedInAll Job Openings

201 - 500 employees

🤖 Artificial Intelligence

Advertising • Artificial Intelligence • Analytics

Vidmob is a company specializing in creative data analytics, offering robust tools and solutions to brand teams, creative teams, media teams, and agencies. The company leverages over 40 proprietary AI models and analyzes trillions of creative elements to improve creative and media decisions. Vidmob provides services like creative scoring, creative analytics, and exports, along with Diversity Measurement and GenAI integration. It partners with major ad platforms to enhance creative effectiveness and media ROI, helping brands to achieve better performance metrics such as increased Click-Through Rates and View-Through Rates. Vidmob is recognized by several prestigious awards for innovation and creativity in advertising and media.

📋 Description

• Lead the design and development of data systems that support analytics, ML/AI products, reporting, APIs, integrations, and customer-facing data products. • Drive ingestion, transformation, modeling, validation, lineage, publishing, and serving across Vidmob’s creative, media, customer, model-output, and performance data. • Architect batch and near-real-time pipelines that are scalable, observable, replayable, and cost-efficient. • Partner with Data Science to turn models, scores, embeddings, prompts, evaluations, and experimental outputs into reliable production data products and customer-facing capabilities. • Build data foundations for AI-powered products using LLMs, VLMs, multimodal analysis, agent workflows, and reinforcement learning. • Establish best practices for data contracts, pipeline design, testing, reviews, observability, and production readiness. • Build governed datasets and serving patterns that support dashboards, APIs, exports, partner integrations, ML workflows, benchmarks, and agent-ready use cases. • Build reliable data flows with ad platforms, DSPs, measurement partners, creative systems, customer environments, and internal product surfaces. • Influence long-term decisions around tooling, storage, processing frameworks, serving patterns, governance, and cost structure.

🎯 Requirements

• 8+ years in data engineering, data platform engineering, or analytics engineering in SaaS, platform, AdTech, MarTech, marketplace, or other data-heavy environments. • Deep experience with modern warehouse, lakehouse, orchestration, and transformation technologies including Snowflake, Databricks, and BigQuery, as well as relational and noSQL databases. • Production-grade SQL and strong programming skills in Python, Scala, Java, or similar languages. Typescript a plus. • Experience designing batch, incremental, and near-real-time processing systems at scale. • Experience designing high-volume processing pipelines and the architecture surrounding them. • Experience building or supporting production products powered by ML or AI, ideally including LLMs, VLMs, embeddings, recommendation systems, or multimodal data products. • Strong ability to productionize models, monitor model outputs, build feedback loops, and make experimental work reliable at product scale. • Experience implementing validation, monitoring, lineage, alerting, incident response, and data trust practices for critical pipelines and model-output workflows. • You actively use AI tools to accelerate development, testing, documentation, data discovery, root-cause analysis, and operational workflows. • You know when to build reusable platform patterns, when to ship tactical fixes, and how to keep one-off work from becoming permanent architecture. • Excellent writing and artifact discipline. You can explain architecture, data quality risks, and tradeoffs clearly across technical and non-technical audiences. • Familiarity with AdTech, MarTech, platform APIs, ML-powered products, or customer-facing analytics products is a major plus. • B2+ written and spoken English required. • You own outcomes, not just pipelines.

🏖️ Benefits

• Periodic international travel within Latam or to the US will be required.