Data EngineerSkills & Competency Framework
What skills does a entry-level Data Engineer in Finance need?
An entry-level Data Engineer in Finance builds and maintains the data infrastructure that powers risk analytics, regulatory reporting, and trading systems. This role requires strong programming fundamentals combined with understanding of financial data structures, compliance requirements, and the low-latency demands of financial institutions. Early-career engineers focus on building reliable pipelines for market data, transaction processing, and regulatory submissions while learning industry-specific security and governance standards.
Primary Skills
Financial Data Pipeline Development
technicalBuilding ETL/ELT pipelines for market data feeds, transaction records, and reference data. Handles high-volume financial data with attention to data integrity, reconciliation, and audit trail requirements specific to financial services.
SQL & Financial Data Modeling
technicalWriting complex SQL for data transformation and analysis of financial instruments, positions, and risk metrics. Designs schemas that accommodate multi-asset class data, temporal versioning, and the complex relationships in financial data.
Programming & Automation
technicalProficiency in Python, Java, or Scala for data processing, API integration, and automation of financial data workflows. Applies clean coding practices, unit testing, and version control to ensure reliability in production financial systems.
Additional Skills
Regulatory Data & Compliance Awareness
operationalUnderstanding the data requirements for financial regulations including Basel III, MiFID II, Dodd-Frank, and AML/KYC reporting. Ensures pipelines meet data lineage, auditability, and retention requirements mandated by regulators.
Data Quality & Reconciliation
operationalImplementing validation checks, cross-system reconciliation processes, and data quality monitoring for financial datasets. Builds automated controls that detect discrepancies in position data, P&L calculations, and regulatory submissions.
Data Security & Access Control
operationalImplementing encryption, masking, and role-based access controls appropriate for sensitive financial data. Understands data classification requirements and maintains compliance with information security policies and regulatory mandates.
Communication & Documentation
interpersonalCreating clear technical documentation for pipelines, data models, and operational procedures. Communicates with trading, risk, and compliance teams to gather requirements and explain data system capabilities and limitations.
Market Data & Reference Data Management
technicalWorking with market data providers, exchange feeds, and reference data systems including security master databases. Understands financial instrument identifiers, corporate actions, and the operational requirements of real-time and end-of-day data delivery.
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Generated by Kaairo's Competency Framework Generator on March 24, 2026