Data Engineer

MediaRadar

9h • Remote

About The Position

MediaRadar equips marketing, sales, and analytics leaders with the intelligence they need to stay ahead. Our platform delivers always-on, AI-enabled Creative, Competitive, Commercial, and Market Intelligence—spanning ad strategy, media spend, creative assets, and brand messaging across 30+ media channels and five million brands. With deep insights into more than 35 million ad and campaign assets and $280 billion in media spend, MediaRadar provides a single, interoperable source of truth that plugs seamlessly into enterprise analytics and AI systems. The result: faster, cleaner, and more actionable intelligence that drives competitive advantage. We are looking for a Data Engineer who can join our Madrid-based team and help build the next generation of our data delivery platform, working closely with senior and principal engineers and engineering leadership across North America and India to design, build, and operate the pipelines that move and transform millions of data points every day. We are deliberately moving away from a locked-in, vendor-heavy stack toward a flexible, largely open-source architecture that keeps our options open. You will be in the engine room of that re-architecture — writing code, designing schemas, tuning queries, and helping prove out new tools before we adopt them at scale. This is a hands-on builder role rather than a pure-architecture one — the deep platform-architecture and strategy ownership sits with our Senior / Principal Data Engineers, whom you will work alongside. You will spend your time building and operating production pipelines, tuning databases, and helping prove out the open-source tools that will shape our platform going forward.

Requirements

• 4-7+ years in data engineering / ETL, with a strong track record as a hands-on engineer building and operating production data pipelines
• Strong SQL and RDBMS skills with solid, hands-on experience schema design, performance tuning, complex query optimization
• Hands-on experience with tools such as dbt, ClickHouse, and open-source pipeline / orchestration tools (e.g., Airflow, Dagster), with the judgment to choose the right tool for the job
• Strong proficiency in Python (or a similar language) for building and automating data pipelines
• Hands-on experience using AI coding assistants and effective prompting techniques (e.g., GitHub Copilot, Claude, ChatGPT), with the judgment to verify, test, and refine AI-generated code and queries
• Hands-on experience with a major cloud platform; AWS strongly preferred, as we are standardizing on AWS as we move off Azure Databricks
• Comfortable with Git, code reviews, and writing tested, maintainable, well-documented code
• Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Nice To Haves

• Experience with cloud data warehouses or lakehouse patterns (Snowflake, BigQuery, Redshift, or similar)
• Experience with streaming / real-time data technologies such as Kafka
• Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code (e.g., Terraform)
• Previous experience in Advertising, Media, or Market Research

Responsibilities

• Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently
• Build and maintain production data workflows using tools such as dbt, ClickHouse, and open-source orchestration frameworks (Airflow, Dagster, or similar)
• Write and optimize complex SQL — schema design, indexing, performance tuning, query optimization, and root-cause analysis
• Contribute to the hands-on migration away from Azure Databricks toward a more open, flexible, AWS-based stack, minimizing disruption to high-volume daily data delivery
• Help build proofs-of-concept to benchmark new tools and patterns, and feed clear results back into the team's adoption decisions
• Use AI coding assistants and well-crafted prompts to accelerate pipeline development, SQL generation, debugging, testing, and documentation — always reviewing and validating output before it ships
• Implement testing, validation, monitoring, observability, and CI/CD practices so data stays accurate and pipelines stay healthy at scale
• Understand the systems upstream and downstream of your pipelines, from ingestion through to client-facing platforms, to ensure clean, end-to-end data delivery
• Partner with engineers in North America and India, participate in code reviews, and learn the nuances of the Advertising and Market Research domain

Benefits

• Inclusive and accessible workplace
• Diversity of backgrounds, perspectives, and experiences
• Equal Opportunity Employer
• Fair and equitable hiring practices
• Pay equity considerations
• Reasonable accommodation during the application or interview process

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level