About WalletConnect WalletConnect is one of the core infrastructure teams in Web3 — we build the connectivity layer that lets wallets and apps communicate securely across blockchains. Since launching in 2018, we’ve grown into a network of 75,000+ apps, 700+ wallets, and 50+ million users. Our mission is to power the financial internet by making digital ownership and payments interoperable and accessible. We’ve recently launched WalletConnect Pay — a payments solution that lets merchants and payment providers leverage blockchain rails for new payment experiences, like stablecoin checkout, payouts, and deposits. Backed by $38M from investors like Union Square Ventures, Shopify, Coinbase Ventures, Circle Ventures, and Uniswap Labs, we’re a global, remote-first team that values openness, simplicity, innovation, and ownership. Why Now We’re entering our most ambitious chapter yet. WalletConnect Pay is an end-to-end crypto and stablecoin payment method built on the world’s largest wallet network — already embedded in Stripe, Coinbase Commerce, Shopify, MoonPay, Shift4, and BitPay, with a landmark partnership with Ingenico bringing stablecoin payments to 40M+ terminals across 120+ countries. As WalletConnect scales into payments, data is becoming foundational — not optional. From wallet connection success rates and transaction health to financial reconciliation, merchant reporting, and operational monitoring, our data systems must be as reliable as the payment flows they track. We’re building a next-generation data platform to support real-time payments infrastructure, developer tooling, and product analytics. This hire joins at the moment we’re moving from MVP pipelines to scalable production architecture, and we need a senior engineer who can help design and operate the data foundation behind a global payments network. The Role This is a Senior Data Engineer position on the Data Engineering team. You’ll work closely with the Data Engineering Lead to design and scale the data platform powering WalletConnect’s payments infrastructure and ecosystem analytics. This role sits at the intersection of data engineering and backend systems. You’ll build and operate event-driven data pipelines, maintain real-time processing systems, and ensure data quality across high-volume transactional workflows. You’ll also build backend services that expose data to internal platforms and APIs, so teams across the company can consume it. Day-to-day, you’ll work with Python, SQL, ClickHouse, Airflow, and dbt within an event-driven architecture. You’ll own the systems you build end-to-end — including monitoring, reliability, and data correctness — and collaborate with product, engineering, and infrastructure teams to support new data use cases as the platform grows. Requirements Data Platform & Pipeline Engineering 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. Data Quality & Observability 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. Backend Services & Data Access 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. Ownership & Operations 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. Tech Stack Our current stack includes Python, SQL, ClickHouse, Airflow, dbt, Grafana, and Preset / Deepnote for data visualization. The architecture is event-driven with near real-time processing. Rust is a plus but not required. We’re also experimenting with AI-assisted monitoring and data tooling as part of our platform evolution. What You Bring Must-Haves 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-Haves Experience in fintech, payments, or financial infrastructure — reconciliation, settlement, ledger reporting, or merchant data. Experience working with high-volume event