MLabs
Decentralized web (Web3)
SeniorDataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior Data Engineer at MLabs. Skills: Data pipelines, Financial data, Backend systems, Event-driven architecture. Design scalable data pipelines. Operate scalable data pipelines”
Industry & Context.
System design; Data architecture; High-volume pipelines; Logic; Approach
What They're Looking For.
Must Have
5+ years data engineering, 5+ years data infrastructure, Expert-level SQL skills, Python programming experience, Experience with Airflow, Experience with dbt, Experience with ClickHouse, Experience with BigQuery, Experience with Snowflake, Experience with Athena, Deep understanding event-driven architectures, Deep understanding real-time data processing, Deep understanding near real-time data processing, Proficiency using AI-assisted development tools, Experience designing systems with data quality, Experience designing systems with observability
Nice to Have
Fintech experience, Payments experience, Financial infrastructure experience, Reconciliation experience, Settlement experience, Ledger reporting experience, Web3 exposure, Blockchain exposure, Crypto ecosystems exposure, On-chain data experience, Wallet analytics experience, High-volume event data experience, Rust familiarity
What You'll Do.
Design scalable data pipelines
Operate scalable data pipelines
Design near real-time data pipelines
Operate near real-time data pipelines
Evolve architecture to production
Model transactional data
Process transactional data
Model ledger-style data
Process ledger-style data
Support financial reconciliation
Support merchant reporting
Support settlement tracking
Ensure data freshness
Build monitoring systems
Build alerting systems
Build backend services
Maintain backend services
Expose data to platforms
Own systems end-to-end
Monitor system reliability
Contribute to engineering standards
Contribute to operational playbooks
How You'll Work.
Team & Collaboration
Internal platforms; Downstream consumers; Product teams; Engineering teams; Remote-first environment; Asynchronous environment
Full Job Description
**Location: **Remote - Europe **Remote | Full-time** **Compensation: **$110K - $125K We are hiring on behalf of our client who is a premier infrastructure provider within the decentralized web (Web3) ecosystem, serving as the critical connectivity layer for tens of thousands of applications and millions of users globally. Having established a dominant market position, the organization is now expanding its horizons by launching a sophisticated payments solution. This new initiative enables merchants and payment providers to utilize blockchain rails for stablecoin checkouts, payouts, and deposits, already reaching millions of terminals worldwide through strategic global partnerships. The data systems supporting this infrastructure are foundational to the company's success. As the organization transitions from MVP pipelines to a scalable production architecture, there is a need for a **Senior Data Engineer** to join the team. This individual will help design and operate the data foundation behind a global payments network, ensuring that systems tracking wallet connections, transaction health, and financial reconciliations are as reliable as the payment flows themselves. This role sits at the intersection of data engineering and backend systems. The successful candidate will build event-driven pipelines, maintain real-time processing systems, and develop backend services that expose critical data to internal platforms and APIs. **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 work
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