MLabs
Senior Data Engineer
Vaga remota de Data Engineering com fit claro de localização do candidato.
Publicada3 de jul. de 2026
Países elegíveis38 países aceitos
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Resumo da vaga
Senior Data Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Key Responsibilities
- Data Platform & Pipeline Engineering: Design and operate scalable, near real-time data pipelines for payment and platform data. Evolution of the current architecture from MVP status to a high-availability production environment is a primary focus.
- Financial Data Modeling: Model and process complex transactional and ledger-style data to support financial reconciliation, merchant reporting, and settlement tracking.
- Data Quality & Observability: Ensure the accuracy and freshness of data across critical workflows. This includes building robust monitoring and alerting systems that meet the stringent reliability standards of financial infrastructure.
- Backend & API Development: Build and maintain backend services to expose data to internal platforms and downstream consumers, ensuring clean integration points for product and engineering teams.
- Operational Ownership: Own systems end-to-end, from initial deployment to ongoing monitoring and reliability. This includes contributing to engineering standards and operational playbooks within a remote-first, asynchronous environment.
Minimum Qualifications:
- Professional Experience: 5+ years of experience in data engineering or data infrastructure, with a proven track record of shipping and operating production-grade systems.
- Technical Proficiency: Expert-level SQL skills and strong programming experience in Python or similar backend languages.
- Modern Data Stack: Significant experience with tools such as Airflow, dbt, ClickHouse, BigQuery, Snowflake, or Athena.
- Architectural Knowledge: Deep understanding of event-driven architectures and real-time/near real-time data processing.
- AI Integration: Proficiency in using AI-assisted development tools and agents, maintaining high discipline in validating and productionizing generated code.
- Reliability Mindset: Experience designing systems where data quality and observability are treated as first-class concerns.
Preferred Qualifications:
- Sector Expertise: Previous experience in Fintech, payments, or financial infrastructure (specifically reconciliation, settlement, or ledger reporting).
- Industry Context: Exposure to Web3, blockchain, or crypto ecosystems (on-chain data or wallet analytics).
- System Scale: Experience handling high-volume event data at scale within a fast-growing startup environment.
- Languages: Familiarity with Rust is considered a strong plus.
Benefits
- Remote-First Culture: Fully remote position with a dedicated budget for home office setup.
- Global Engagement: Opportunities for regular team offsites at international locations and travel to industry conferences.
- Professional Growth: Meaningful Learning & Development budget to support continuous skill acquisition.
- Comprehensive Leave: Generous Paid Time Off (PTO) and parental leave policies.
- Competitive Package: Compensation includes salary and equity components.
- Healthcare: Coverage provided for US-based team members.
Interview Process
- System Design: Focused on data architecture and high-volume pipelines.
- Practical Assessment: A problem-solving exercise focused on logic and approach.
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