Staff Data Engineer

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Who we are:

Welcoming, collaborative and having the opportunity to make an impact - is how our employees describe working here. Galileo is a financial technology company that provides innovative and revolutionary software products and services that power some of the world's largest Fintechs. We are the only payments innovator that applies tech and engineering capabilities to empower Fintechs and financial institutions to unleash their full creativity to achieve their most inspired goals. Galileo leads its industry with superior fraud detection, security, decision-making analytics and regulatory compliance functionality combined with customized, responsive and flexible programs to accelerate the success of all payments companies and solve tomorrow's payments challenges today. We hire energetic and creative employees while providing them the opportunity to excel in their careers and make a difference for our clients. Learn more about us and why we work here at https://www.galileo-ft.com/working-at-galileo.

We’re looking for a Staff Data Engineer who can see the big picture, make smart architectural calls, and still deliver in small, well-scoped steps. You’ll help define how Galileo’s cloud-native data platform evolves, from how we model and move data to how teams across the company (and our clients) access and rely on it. Your work will shape the standards and technical direction that multiple squads build on.

In this role, you’ll take ownership of complex cross-team initiatives, establish clear technical direction, and raise operational standards. You pair strong technical instincts with clear, steady communication, and you can turn ambiguity into well-sequenced, actionable work. You’ll help shape both the platform and the way our team works. If you thrive in iterative delivery, enjoy solving complex data problems, and want your work to actually matter, you’ll fit right in.

• Shape the architecture of Galileo’s cloud-native, multi-tenant data platform, defining patterns and workflows used by internal teams and external clients.
• Design domain data models, contracts, and semantic layers that improve clarity, trust, and consistent analytical and operational use across the business.
• Build and evolve reusable platform components that raise engineering standards and eliminate one-off, pipeline-by-pipeline work.
• Lead strategy for automated data quality, lineage, and observability, moving us toward metadata-driven systems with clear SLOs.
• Drive complex cross-team initiatives, creating clarity, aligning stakeholders, and guiding architectural decisions that move the platform forward.
• Resolve systemic platform issues through durable improvements that enhance performance, reliability, and developer productivity.
• Partner with Product, Platform, Security, and Analytics to align priorities and connect technical decisions to broader organizational goals.
• Raise engineering standards through strong design reviews, improved CI/CD practices, and automation that reduces operational load.
• We’re looking for someone who not only raises the technical bar, but also strengthens our small, high-trust team through thoughtful communication, ownership, and a genuine commitment to being a culture add.

• 8+ years of professional data platform engineering experience, with proven depth leading complex, cross-team initiatives and evolving long-lived systems.
• Expert-level SQL and strong proficiency in Python or Java, with a track record of building reliable, maintainable, well-tested data systems.
• Deep Snowflake expertise, including architectural design, warehouse optimization, cost/performance trade-offs, data sharing, and advanced platform features.
• Strong experience in a major cloud environment (AWS preferred), designing systems that are secure, scalable, observable, and aligned to best practices.
• Expertise with workflow orchestration (Airflow preferred) and transformation frameworks (dbt, PySpark, Snowpark).
• Experience shaping BI or semantic layers ensuring durable, consistent definitions across domains.
• Strong grounding in Git-based workflows and CI/CD, with the ability to improve engineering practices, reduce operational friction, and raise release reliability across squads.
• Demonstrated Staff-level leadership - creating clarity from ambiguity, making sound architectural trade-offs, mentoring across teams, and driving alignment through clear, direct communication.