Data Engineering Manager

• Team Leadership & Mentorship: Lead and mentor data engineers on the Madrid team, providing clear technical direction and constructive code reviews, while partnering closely with distributed engineers across North America and India • Hands-On Delivery & Pipeline Ownership: Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently — staying hands-on in the code rather than delegating it away • AI-Assisted Development: Champion the use of AI coding assistants and prompt-based development to accelerate prototyping, code generation, refactoring, testing, and documentation, and establish best practices and review standards for your team • Hands-On POCs & Prototyping: Personally build proofs-of-concept to validate new tools and patterns (e.g., ClickHouse, dbt, open-source orchestration frameworks) before broader rollout, and translate results into clear recommendations • Platform Modernization: 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 • Deep System Integration: Understand the systems upstream and downstream of your pipelines, from ingestion through to client-facing platforms, to ensure clean, end-to-end data delivery • Operational Excellence: Establish testing, validation, monitoring, observability, and CI/CD practices that guarantee data integrity at scale • Domain Mastery: Rapidly learn the nuances of the Advertising and Market Research domain to translate business needs into robust technical requirements

What You've Done: • 6-8+ years in data engineering / ETL as a hands-on engineer, with some experience leading, mentoring, or informally guiding other engineers — formal people-management experience is a plus but not a requirement, given the hands-on nature of this role today • Strong SQL and RDBMS skills with solid, hands-on experience in SQL Server and Postgres — schema design, performance tuning, and 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, Cursor, Claude), with the judgment to verify, test, and refine AI-generated code and queries — and the ability to set standards for how a team uses these tools • Hands-on experience with a major cloud platform; AWS strongly preferred, as we are standardizing on AWS as we move off Azure Databricks • Demonstrated ability to independently prototype, benchmark, and evaluate new technologies, translating results into clear, pragmatic adoption decisions • 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 • Professional fluency in written and spoken English: Strong communication skills to effectively collaborate with distributed engineering, product, and business teams across North America, India, and Europe. What You'll Do: • Team Leadership & Mentorship: Lead and mentor data engineers on the Madrid team, providing clear technical direction and constructive code reviews, while partnering closely with distributed engineers across North America and India • Hands-On Delivery & Pipeline Ownership: Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently — staying hands-on in the code rather than delegating it away • AI-Assisted Development: Champion the use of AI coding assistants and prompt-based development to accelerate prototyping, code generation, refactoring, testing, and documentation, and establish best practices and review standards for your team • Hands-On POCs & Prototyping: Personally build proofs-o

At MediaRadar, we are committed to creating an inclusive and accessible workplace where everyone can thrive. We believe that diversity of backgrounds, perspectives, and experiences makes us stronger and more innovative. We are proud to be an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other legally protected status. In accordance with the EEO-1 reporting requirements, we collect demographic data as part of our efforts to ensure fair and equitable hiring practices across all levels of our organization. A final compensation offer will ultimately be based on the candidate's location, skill level and experience, and the Company's pay equity. We are also committed to ensuring our recruitment process is accessible to all applicants. If you need a reasonable accommodation during the application or interview process, please contact us at careers@mediaradar.com. We’re excited to meet people who share our values and want to build the future with us.

Location: Madrid, Spain (Remote — with regular in-person collaboration at a local WeWork alongside our Madrid tech team) About MediaRadar 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. About The Role: We are looking for a Data Engineering Manager to join our Madrid-based team and take ownership of our data delivery lifecycle — driving the end-to-end delivery of complex data projects while managing and mentoring a growing team of data engineers. This is a player-coach role: at least for now, you will remain deeply hands-on — writing code, designing schemas, and building proofs-of-concept alongside your team — rather than stepping into a purely managerial capacity. We are deliberately moving away from a locked-in, vendor-heavy stack (e.g., Azure Databricks) 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 tools such as ClickHouse, dbt, and open-source orchestration frameworks before we adopt them at scale — while also mentoring your team to do the same and championing AI-assisted development practices (e.g., GitHub Copilot, Cursor, Claude) across the group. What You've Done: • 6-8+ years in data engineering / ETL as a hands-on engineer, with some experience leading, mentoring, or informally guiding other engineers — formal people-management experience is a plus but not a requirement, given the hands-on nature of this role today • Strong SQL and RDBMS skills with solid, hands-on experience in SQL Server and Postgres — schema design, performance tuning, and 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, Cursor, Claude), with the judgment to verify, test, and refine AI-generated code and queries — and the ability to set standards for how a team uses these tools • Hands-on experience with a major cloud platform; AWS strongly preferred, as we are standardizing on AWS as we move off Azure Databricks • Demonstrated ability to independently prototype, benchmark, and evaluate new technologies, translating results into clear, pragmatic adoption decisions • 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 • Professional fluency in written and spoken English: Strong communication skills to effectively collaborate with distributed engineering, product, and business teams across North America, India, and Europe. What You'll Do: • Team Leadership & Mentorship: Lead and mentor data engineers on the Madrid team, providing clear technical direction and constructive code reviews, while partnering closely with distributed engineers across North America and India • Hands-On Delivery & Pipeline Ownership: Design, build, and optimize robust ETL/ELT pipelines that move and transform millions of daily data points reliably and efficiently — staying hands-on in the code rather than delegating it away • AI-Assisted Development: Champion the use of AI coding assistants and prompt-based development to accelerate prototyping, code generation, refactoring, testing, and documentation, and establish best practices and review standards for your team • Hands-On POCs & Prototyping: Personally build proofs-of-concept to validate new tools and patterns (e.g., ClickHouse, dbt, open-source orchestration frameworks) before broader rollout, and translate results into clear recommendations • Platform Modernization: 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 • Deep System Integration: Understand the systems upstream and downstream of your pipelines, from ingestion through to client-facing platforms, to ensure clean, end-to-end data delivery • Operational Excellence: Establish testing, validation, monitoring, observability, and CI/CD practices that guarantee data integrity at scale • Domain Mastery: Rapidly learn the nuances of the Advertising and Market Research domain to translate business needs into robust technical requirements Bonus Points (Nice to Haves) • Previous experience in Advertising, Media, or Market Research • Familiarity with containerization (Docker, Kubernetes) and infrastructure-as-code (e.g., Terraform) • Experience with streaming / real-time data technologies such as Kafka A Little More About The Role This is a hands-on, player-coach role rather than a pure people-management position — for now, you will spend the majority of your time building and operating production pipelines, tuning databases, and helping prove out the open-source tools that will shape our platform going forward, while also providing technical direction and mentorship to the engineers around you. This role is remote-based in Madrid, with the expectation that you'll join the team in person at a local WeWork space perio