Lead Data Engineer

About the Company: We are partnering with a high-growth rewards and loyalty platform that sits at the intersection of consumer engagement, mobile gaming, and adtech. Their platform rewards millions of active users for engaging with apps and games while delivering measurable, high-ROI acquisition campaigns for global advertisers. In this ecosystem, data isn't just a back-office support function, it is the core product. Every reward paid out, every game surfaced to a user, and every advertiser dollar attributed relies on the pipelines and real-time infrastructure built by the data team. About the Role: We are looking for a Lead Data Engineer to design, scale, and own the data architecture that processes millions of events daily across a high-traffic consumer rewards app and digital advertising network. In addition to driving deep technical excellence, you will build, hire, and lead a high-performing data engineering team from the ground up. If you are a deeply technical leader who thrives on building scalable systems zero-to-one and mentoring top engineering talent, this is your next high-impact role. Responsibilities: Leadership & Team Building . Hire, mentor, and lead a world-class team of data engineers.. Define the technical roadmap, set data engineering standards, and establish best practices across the organization. Architecture & Scalability . Take platform challenges from zero-to-one.. Design and build scalable integrations across product, payment, advertising, and partner systems pulling data from APIs, databases, events, and webhooks. End-to-End Pipeline Ownership . Own data flows bi-directionally—managing high-throughput ingestion into modern cloud warehouses as well as reverse ETL pipelines into operational tools. Real-Time Data Processing . Build event-driven, high-frequency ingestion systems capable of processing real-time and asynchronous streams at volume. Data Modeling & Governance . Model and transform complex datasets using dbt to create clean, reusable, and trusted data structures for downstream analytics and ML. Infra & DevOps . Ship cloud infrastructure as code (IaC) and maintain CI/CD pipelines.. Own services end-to-end, from API design to automated deployment and monitoring. Observability & Cost Management . Establish robust systems to monitor failure rates, data freshness, latency, and quality while optimizing cloud infrastructure costs. What We’re Looking For: Proven Leadership: Experience mentoring engineers and a strong desire or proven ability to recruit, grow, and lead a data engineering function. Production Mastery : Extensive background operating high-reliability, large-scale data platforms in production environments. Core Technical Skills: Mastery of Python, advanced SQL, data modeling, incremental processing, and schema evolution. Cloud & Warehouse Expertise: Strong hands-on experience with modern cloud data warehouses (Snowflake, BigQuery) and AWS/GCP platforms. Software Engineering Fundamentals: Solid foundation in Git, Docker, CI/CD, testing, and Infrastructure as Code (Terraform). Transformation & Ingestion: Proficiency with dbt (or similar transformation frameworks) and experience managing event-driven architectures, APIs, and partner webhooks. Mindset: Pragmatic approach with a bias toward simple, scalable solutions; excellent communication skills; and high operational ownership. Nice-to-Have: Data & Storage: Snowflake, BigQuery, Postgres, dbtCloud & Infra: AWS, GCP, Terraform, DockerLanguages: Python, SQL, TypeScriptTooling: Airbyte, Hex, GitHub Actions, Git Note: You don't need experience with every single tool in this stack, strong engineering fundamentals, architecture skills, and team-building capability matter most. What’s on Offer:Fully remote flexibility within Europe.Opportunity to build and structure your own data engineering team from scratch.High visibility and direct impact on core business metrics and user-facing features.