Senior Data Engineer — Real-Time Payments (Remote)

Reown; New York (NY); À distance; USD 140 000 - 190 000; Plein temps

Avantages offerts par ce poste

Fully remote

Team offsites

Learning & development budget

Competitive compensation

Résumé du poste

WalletConnect is hiring a Senior Data Engineer to design, build, and operate scalable data pipelines powering payments and analytics. You will own end-to-end data platforms, ensuring reliability and data quality across high-volume transactions.

You will work with Python, SQL, ClickHouse, Airflow, and dbt in an event-driven setup, collaborating with product, engineering, and infra teams to enable new data use cases at scale.

Qualifications

• 5+ years of experience in data engineering or data infrastructure.
• Built, shipped, and operated production data systems.
• Strong SQL and large-scale data processing experience.
• Experience with modern data stack tools: Airflow, dbt, ClickHouse, BigQuery, Snowflake, Athena.
• Teamwork in event-driven architectures and real-time data processing.
• Exposure to Web3, blockchain, or crypto data ecosystems.

Responsabilités

• Design, build, and operate scalable data pipelines for payments and platform analytics.
• Maintain and evolve the real-time data platform from MVP to production scale.
• Ensure data accuracy, freshness, and observability across critical workflows.

Connaissances

SQL

Python

Data pipelines

Real-time processing

Data quality & observability

Event-driven architecture

Remote async collaboration

Web3 data

Outils

Airflow

dbt

ClickHouse

BigQuery

Snowflake

Athena

Grafana

Presets/Deepnote

Description du poste

WalletConnect is hiring a Senior Data Engineer to design, build, and operate scalable data pipelines powering payments and analytics. You will own end-to-end data platforms, ensuring reliability and data quality across high-volume transactions.

You will work with Python, SQL, ClickHouse, Airflow, and dbt in an event-driven setup, collaborating with product, engineering, and infra teams to enable new data use cases at scale.