Staff Data Engineer

Role Overview

• 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.

Tech Stack

• BigQuery
• Java
• NoSQL
• Python
• Scala
• SQL
• TypeScript

Benefits

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