Responsibilities
- Design, build, and operate scalable data pipelines for WalletConnect payments and platform data — event-driven, near real-time processing across high-volume transaction flows.
- Maintain and evolve the real-time data platform, moving it from MVP pipeline to scalable production architecture.
- Model and process transactional and ledger-style data — financial reconciliation, merchant reporting, wallet fee breakdowns, and settlement tracking.
- Contribute to improving the overall data platform architecture as requirements grow.
- Ensure data accuracy, freshness, and observability across critical workflows — payments flow correctness, wallet connection success rates, and transaction health.
- Build monitoring and alerting that meets the reliability bar required for financial data systems.
- Own data quality across the pipeline — from ingestion through transformation to downstream consumption.
- Develop backend services that expose data to internal platforms, APIs, and downstream systems so teams across the company can consume it.
- Support downstream use cases including financial reconciliation, merchant reporting, operational monitoring, and product analytics.
- Collaborate with product, engineering, and infrastructure teams to onboard new data use cases and ensure clean integration points.
- Own and operate the systems you build, including deployment, monitoring, and reliability.
- Collaborate closely with the Data Engineering Lead on architecture decisions and platform evolution.
- Contribute to engineering standards, documentation, and operational playbooks for the data platform.
Requirements
- 5+ years of experience in data engineering or data infrastructure — you’ve built, shipped, and operated production data systems.
- Strong experience building data pipelines and production data platforms — ingestion, transformation, modelling, and serving.
- Comfortable using AI-assisted development tools/agents, with strong discipline in reviewing, validating, and productionizing generated code.
- Expertise in SQL and large-scale data processing.
- Experience with modern data stack tools: Airflow, dbt, ClickHouse, BigQuery, Snowflake, Athena, or similar.
- Experience working with event-driven architectures and real-time or near real-time data processing.
- Strong programming skills in Python or similar backend languages.
- Experience designing systems with data quality, monitoring, and reliability in mind — you treat data correctness as a first-class concern.
- Ability to operate independently and own production systems end-to-end in a remote, async team.
Nice to Have
- Experience in fintech, payments, or financial infrastructure — reconciliation, settlement, ledger reporting, or merchant data.
- Experience working with high-volume event data at scale.
- Familiarity with ledger-style or transactional data models.
- Exposure to Web3, blockchain, or crypto ecosystems — on-chain data, wallet analytics, or token transaction flows.
- Rust experience or willingness to learn.
- Experience building data platforms in fast-growing startups where you’ve shaped the architecture from early stages.
