Summary:
Design, build, and maintain scalable data infrastructure and pipelines that support banking operations, analytics, and regulatory compliance. This role bridges technical leadership with strategic business needs, ensuring data is accurate, secure, and accessible.
Key Responsibilities:
Data Architecture & Pipeline Development
Design and implement robust, scalable data pipelines for structured and unstructured data.
Oversee ETL/ELT processes to ingest data from core banking systems, CRM, and external sources.
Ensure data models support real-time analytics, reporting, and machine learning.
Collaborate with
data scientists and analysts to provide usable, cleaned and aggregated data to end users
Governance, Security & Compliance
Ensure data practices comply with banking regulations (e.g., Basel III, GDPR, local laws).
Implement data governance frameworks, including metadata management and lineage tracking.
Collaborate with cybersecurity teams to safeguard sensitive financial data.
Performance Optimization
Monitor and optimize data infrastructure for performance, reliability, and cost-efficiency.
Troubleshoot data issues and ensure high availability of data services.
Innovation & Tooling
Evaluate and adopt modern data technologies (e.g., cloud platforms, data lakes, streaming tools).
Promote automation and DevOps practices in data engineering workflows.
Qualifications:
Bachelor's or Master's in Computer Science, Data Engineering, or related field.
At least 7 years in data engineering, with 2+ years in a leadership role.
Strong experience with SQL, Python/Scala, Spark, Kafka, and cloud platforms (AWS/GCP/Azure).
Familiarity with banking systems, financial data structures, and regulatory requirements.
Excellent communication and stakeholder management skills.