Senior Data Engineer

What you'll do

• Design and implement core components of our data pipelines and services in Go and Scala, with a focus on scalability, performance, and long-term maintainability.
• Partner closely with engineers, analysts, and product stakeholders to design solutions for strategic initiatives, business-critical data products, and agentic AI architectures.
• Contribute to the evolution of our data platform architecture, improving scalability, reliability, observability, and data correctness across the stack.
• Build and curate high-quality, well-modeled, and richly contextual datasets that power internal products, predictive analytics, and LLM-enabled features at company scale.
• Develop a deep understanding of the company’s data ecosystem — including source systems, tooling, and data flows — and collaborate closely with the data and system engineers in Austin, Lisbon, and London to improve data ingestion, quality, and governance.
• Lead by example through design reviews, knowledge sharing, and mentorship, helping raise the technical bar, data engineering practices, and AI implementation standards across the organization.

Requirements

• B.S. or M.S. in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field, or equivalent practical experience.
• 5+ years of professional experience in data engineering, software engineering, or related roles, building and operating production data systems.
• Strong programming expertise in Go, Python, or JVM-based languages, with experience writing high-quality, production-grade services and pipelines.
• Deep knowledge of SQL and hands-on experience designing data models and working with relational, analytical, or vector databases (e.g., PostgreSQL, MySQL, ClickHouse).
• Experience building scalable, reliable, and observable data pipelines, with an understanding of performance, data quality, and operational best practices.
• Proven problem-solving and communication skills, with a track record of driving projects in ambiguous environments and partnering effectively with cross-functional teams.

Nice-to-haves

• Familiarity with container based deployments such as Docker & Kubernetes.
• Familiarity with Google Cloud Platform, foundational Large Language Model (LLM) orchestration frameworks, or something similar.