Data Engineer
Summary
Data Engineer at a global fintech company building production-grade data pipelines and distributed infrastructure. Core tech includes Python, SQL, Airflow, and big data platforms like Spark or Flink, with a focus on end-to-end ownership and AI/LLM integration.
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