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Data Engineer

🌐 Remote💼 Full-time💰 $60,000–$100,000🗓 2026-09-24 → 2026-09-28

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

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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