Data Engineer

Our client is a fast-growing, global fintech company operating at the intersection of technology and financial services. They are trusted by millions of users and institutions worldwide, and are known for a strong engineering culture built on ownership, speed, and doing the right thing.

About the Role

We're looking for a Data Engineer to help design, build, and own critical data pipelines and platform capabilities that power the business. You'll work end-to-end — from ingestion through modeling to downstream consumption — with reliability, scalability, and data quality as first-class requirements. You'll also have the opportunity to apply modern AI/LLM tooling to accelerate development, monitoring, and domain ramp-up.

What You'll Be Doing

• Design, build, and maintain production-grade data pipelines (batch and/or real-time) across ingestion, transformation, and serving layers
• Own end-to-end data domains — business logic, data quality, and incident handling — rather than just executing tickets
• Build and maintain scalable distributed data infrastructure (e.g., Spark, Hadoop, Flink, or equivalent big data platforms)
• Design proactive data quality checks, monitoring, and alerting to catch issues before they hit downstream systems
• Apply AI/LLM tooling to accelerate pipeline development, documentation, and domain learning
• Collaborate closely with cross-functional teams (product, compliance, platform, analytics) to translate ambiguous requirements into scoped engineering tasks
• Contribute to platform reliability, cost efficiency, and operational excellence
• Mentor junior engineers as your domain expertise grows

What We Look For In You

• 4+ years of experience in data engineering with strong production pipeline experience (ETL/ELT, SQL, Python, orchestration tools like Airflow or equivalent)
• Strong software engineering fundamentals — Java, Scala, or Python
• Experience with distributed data systems and large-scale storage/compute
• Demonstrated ability to own a data domain end-to-end
• Strong data modeling skills, with attention to auditability, lineage, and correctness
• Comfortable working in ambiguity — able to turn underspecified requirements into concrete engineering plans
• Fast learner, with evidence of ramping up quickly in unfamiliar domains
• Familiarity with LLM/AI tooling applied to data engineering is a strong plus

Technology | GTM | Mid-Senior Level