Data Engineer -- Regulatory Reporting & Portfolio Intelligence

Nium, the Leader in Real-Time Global Payments

Nium, the leading global infrastructure for real-time cross-border payments, was founded on the mission to deliver the global payments infrastructure of tomorrow, today.

With the onset of the global economy, its payments infrastructure is shaping how banks, fintechs, and businesses everywhere collect, convert, and disburse funds instantly across borders. Its payout network supports 100 currencies and spans 190+ countries, 100 of which in real-time.

Funds can be disbursed to accounts, wallets, and cards and collected locally in 40 markets. Nium's growing card issuance business is already available in 34 countries. Nium holds regulatory licenses and authorizations in more than 40 countries, enabling seamless onboarding, rapid integration, and compliance – independent of geography.

The company is co-headquartered in San Francisco and Singapore.

Key Responsibilities

Build and optimize scalable, maintainable, and high-performance data pipelines for regulatory data ingestion, transformation, and delivery.

Develop XML and REST API connectors to integrate data from banking partners, regulatory feeds, internal systems, and risk/compliance platforms.

Implement bit request handlers to support real-time transaction and portfolio data updates for risk monitoring and regulatory reporting.

Work with Compliance, MLRO, and Risk teams to understand regulatory filing and reporting requirements, then design data models and transformations to support them.

Interpret regulatory requirements (sanctions lists, transaction thresholds, portfolio limits, reporting deadlines) and encode them into data logic and quality checks.

Design and maintain efficient data models in cloud data warehousing solutions (e.g., Redshift) optimized for regulatory reporting, audit trail queries, and risk analytics.

Write complex SQL queries and transformations to prepare data for compliance analysis, regulatory submissions, and audit trails.

Ingest and transform both structured (databases, APIs) and semi-structured (XML, JSON) data at scale from diverse compliance and risk sources.

Establish robust data quality checks, monitoring, and alerting mechanisms to ensure data integrity for regulatory compliance and risk control effectiveness.

Support cloud migration initiatives and modernize legacy data pipelines (e.g., on premises to AWS).

Document data pipelines, connectors, and technical architecture for auditability, regulatory inspection readiness, and cross-team knowledge sharing.

Collaborate with Country Compliance, MLRO, Risk, Product, and Data teams to operationalize compliance rules and regulatory logic into scalable systems.

Evaluate effectiveness of data controls, monitoring, and quality checks using testing and validation (e.g., completeness checks, SLA validation, rule effectiveness).

Requirements

3-5 years of professional experience in Data Engineering, ETL/ELT pipeline development, or systems integration

Strong SQL expertise including query optimization, complex transformations, and data modelling.

Solid proficiency in Python (or similar language) for writing data pipelines, scripts, and data processing logic.

Hands-on experience designing and developing API connectors (REST, SOAP) and working with XML/JSON data formats.

Experience with cloud data platforms (AWS Redshift, Snowflake, Google Big Query, or similar) and cloud storage (S3, GCS, etc.)

Familiarity with data orchestration tools (Apache Airflow, Prefect, or equivalent) for workflow automation.

Understanding of data modelling concepts and ability to design efficient schemas for analytical and operational workloads.

Experience with real-time or near-real-time data processing (Kafka, streaming pipelines) is a plus.

Knowledge of data quality frameworks and testing practices for data pipelines.

Strong problem-solving skills and ability to debug complex data integration issues.

Collaborative mindset with ability to work across technical and non-technical stakeholders.

Familiarity with regulatory reporting requirements (e.g., transaction reporting, sanctions screening, KYC/AML, portfolio monitoring) is highly valuable.

Ability to learn and interpret regulatory documentation and translate compliance/risk requirements into technical specifications.