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Data Engineer

🌐 Remote💼 Full-time💰 $60,000–$100,000🗓 2026-09-24 → 2026-09-25

Core

Build and scale the data backbone powering product analytics, operational intelligence, financial reporting, partner reconciliations, and internal platform use cases for a banking & payments infrastructure company.

Role type

Senior backend-heavy data engineer (data platform)

Builds

Robust batch and near-real-time data pipelines, backend data services, and internal data products exposing clean datasets.

Domain

Fintech, banking, payments, and regulated financial infrastructure

Deliverable

production ML models | product features | dashboards & analysis

Required skills

Python, SQL, data modeling, schema design, query optimization, orchestration (Airflow/Dagster/Kafka/Spark), cloud-native infrastructure (AWS/GCP), database design and management, API integration, distributed systems, event-driven architectures, CI/CD, observability, data quality checks, failure recovery, security-conscious data handling, access control, auditability.

Preferred skills

Fintech/banking/lending/payments domain knowledge, reconciliation systems, settlement workflows, ledgering, risk and fraud datasets, data governance, PII protection, encryption, audit trails, BI tooling (Metabase/Looker/Superset), internal developer platforms, data APIs.

Technologies

Python, SQL, Airflow, Dagster, Kafka, Spark, AWS, GCP, Metabase, Looker, Superset

Responsibilities

Design and build robust batch and near-real-time data pipelines for payments, banking, KYC, risk, ledgering, and reconciliation; Develop backend-heavy data services and internal data products; Model and maintain highly scalable data stores, schemas, and ingestion frameworks; Work on integration of new and existing databases ensuring speed, scalability, and reliability; Build and maintain ETL and ELT workflows, orchestration layers, data quality checks, and failure recovery mechanisms; Partner with backend teams to instrument events, improve data contracts, and enable better observability; Optimize SQL, storage design, partitioning, and compute usage for large-scale transactional and analytical workloads; Design systems with strong attention to security, access control, auditability, and compliance-ready data handling.

Seniority

Senior, hands-on IC

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