Senior Data Engineer
Summary
Design and maintain data models for banking systems, ensuring reliable data-driven decisions across domains like loans, payments, and regulatory reporting.
Roles & Responsibilities
The ideal candidate will have extensive experience working with complex banking data across domains such as Customer, Accounts, Deposits, Loans, Payments, Cards, Transactions, Risk, Finance, Treasury, and Regulatory Reporting.
The candidate will work closely with business stakeholders, data architects, technology teams, data engineers, and governance teams to define data requirements, develop enterprise data models, improve data quality, and enable reliable data-driven decision-making.
The role requires a strong understanding of banking business processes combined with hands-on expertise in conceptual, logical, and physical data modelling, data lineage, data integration, metadata management, and modern data architecture.
Design and maintain Conceptual, Logical, and Physical Data Models for banking and enterprise data platforms.
Required Skills
10+ years of overall experience in Data Analysis, Data Management, Data Modelling, Data Architecture, or related roles.
Significant experience within Banking, Financial Services, or regulated financial institutions.
Strong hands-on experience with Conceptual, Logical, and Physical Data Modelling.
Strong knowledge of enterprise data architecture and data management principles.
Proven experience working on large-scale banking data transformation, modernization, migration, regulatory, or analytics programs.
Strong experience in source-to-target mapping, data profiling, data lineage, data quality, and metadata management.
Experience working with enterprise data warehouses, data marts, data lakes, and analytical platforms.
Strong knowledge of relational databases and SQL.
Ability to analyze complex business requirements and translate them into scalable data solutions.
Other Skills
SQL
Oracle / SQL Server / PostgreSQL / DB2 or equivalent relational databases
Data modelling tools such as Erwin or other equivalent tools
ETL / ELT concepts
Data Lakes and Lakehouse architectures & Data governance.