Streamlining Data Workflows: Custom ETL Pipeline for a Financial Client

Project Overview

We were engaged by a financial services firm to build a secure, auditable ETL pipeline for processing sensitive financial data. The client needed to consolidate data from multiple source systems — trading platforms, settlement systems, and market data feeds — into a unified data warehouse for predictive analytics and regulatory reporting. Given the sensitivity of financial data and requirements around transaction integrity, data lineage, and audit trails, the solution demanded enterprise-grade security and compliance controls throughout.

Key Challenges

• Data Sensitivity: Processing included PII (customer details), financial transaction data, and proprietary trading information requiring encryption, access controls, and audit logging throughout the pipeline.
• Regulatory Requirements: The pipeline needed to support MiFID II transaction reporting obligations, requiring complete data lineage from source to report and T+1 reconciliation capabilities.
• Fragmented Infrastructure: Data resided across 12+ source systems with inconsistent schemas, varying update frequencies, and limited API capabilities.
• Operational Visibility: The existing manual scripting approach provided no centralised monitoring, making it impossible to track data freshness, identify failures promptly, or demonstrate compliance to auditors.

Our Solution

• Secure Orchestration Platform: Centralised ETL management with role-based access control, ensuring only authorised personnel can configure pipelines, view sensitive data, or approve production changes.
• Encryption Throughout: Data encrypted in transit (TLS 1.3) and at rest (AES-256). Sensitive columns (account numbers, customer identifiers) additionally protected with column-level encryption and tokenisation.
• Complete Data Lineage: Every record tracked from source extraction through transformation to final load, enabling full audit reconstruction and regulatory reporting compliance.
• Immutable Audit Logs: All pipeline executions, data modifications, and access events logged to tamper-evident storage with 7-year retention.
• Self-Service Administration: Intuitive UI for authorised users to add data sources, configure transformations, and monitor pipeline health — with approval workflows for production changes.

Security & Compliance Architecture

• Access Control: OIDC integration with corporate identity provider. Role-based permissions (Data Engineer, Analyst, Auditor, Admin) with least-privilege defaults. Segregation of duties between development and production environments.
• Data Classification: Automated tagging of sensitive data types (PII, financial, proprietary) with policy-driven handling rules including masking, encryption, and access restrictions.
• Change Management: All pipeline modifications require peer review and approval before production deployment. Version-controlled configurations with rollback capability.
• Monitoring & Alerting: Real-time dashboards showing pipeline health, data freshness, and anomaly detection. PagerDuty integration for critical failures. SLA tracking for regulatory reporting deadlines.
• Audit Support: One-click report generation for auditors showing data lineage, access history, and transformation logic for any record or time period.

Technologies Used

The stack was selected for security, reliability, and enterprise scalability:

• Apache Airflow 2.x: DAG-based workflow orchestration with comprehensive logging, retry policies, and SLA monitoring. Custom operators for secure credential handling and audit logging.
• Docker + Kubernetes: Containerised deployment with namespace isolation, network policies, and secrets management via HashiCorp Vault.
• Dask: Distributed computing for parallel data processing and validation. Handles datasets exceeding 100GB with efficient memory management.
• PostgreSQL 15: Primary metadata store with row-level security, encrypted connections, and point-in-time recovery. Audit logging via pgAudit extension.
• React + TypeScript: Type-safe frontend with comprehensive input validation, CSRF protection, and role-aware UI rendering.
• Great Expectations: Data quality framework for automated validation, schema enforcement, and drift detection with alerting.

Results

The pipeline delivered measurable improvements across operational efficiency, data quality, and compliance posture:

• 60% Reduction in manual data processing time, with automated validation catching data quality issues before they reach downstream systems.
• 100% Audit Coverage: Complete data lineage for every record, enabling the client to satisfy auditor requests within hours rather than weeks.
  
• 99.9% Pipeline Reliability: Automated retry logic, alerting, and self-healing capabilities reduced data delivery failures to near-zero.
  
• T+1 Regulatory Compliance: Transaction reporting now meets regulatory deadlines consistently, with automated reconciliation flagging discrepancies for immediate investigation.
• Zero Security Incidents: 24 months in production with no data breaches, unauthorised access, or compliance violations.

Why NodeNova

What distinguishes NodeNova is our understanding that financial data infrastructure requires more than technical competence — it demands security-first architecture, regulatory awareness, and operational excellence:

• Regulated Industry Experience: We've delivered data infrastructure for FCA-regulated firms, understanding the compliance obligations around data handling, audit trails, and operational resilience.
• Security by Design: Encryption, access control, and audit logging aren't afterthoughts — they're foundational to our architecture approach.
• Production Engineering: We build for operability: comprehensive monitoring, documented runbooks, and incident response procedures.
• Long-term Partnership: We design systems that your team can operate, extend, and maintain — with ongoing support as your needs evolve.

Long-term Impact

We maintain an ongoing partnership with the client, providing:

• Quarterly Security Reviews: Vulnerability assessments, access audits, and security posture updates aligned to evolving threats.
• Capacity Planning: As data volumes grow (3x increase in 18 months), we've scaled infrastructure while maintaining performance SLAs.
• Regulatory Adaptation: When new reporting requirements emerge, we extend the pipeline to capture additional data points and generate required outputs.
• Knowledge Transfer: Comprehensive documentation and training ensures the client's team can operate the system independently while we remain available for strategic enhancements.