Job Title: Lead Data Engineer / Architect (FSLDM & Data Lakehouse)
Experience: 10+ Years
Project: International Financial Data Lakehouse Program
Duration: 6 Months initially
Location: Remote
Role Objective
We are seeking a seasoned Data Professional to drive the design and implementation of a modern Data Lakehouse for a major financial services program. The ideal candidate will be an expert in the Teradata FSLDM framework and possess deep expertise in Informatica for complex ETL/ELT orchestration. You will be responsible for transforming raw financial data into a structured, high-performance Lakehouse architecture that supports both BI and advanced analytics.
Key Responsibilities
- Data Modeling: Lead the implementation and customization of the Teradata FSLDM (Financial Services Logical Data Model) to ensure it meets the specific needs of the Lakehouse program.
- Architecture Design: Design and maintain the Data Lakehouse layers (Bronze/Silver/Gold or Raw/Integrated/Access) to support massive scales of financial data.
- ETL/ELT Development: Architect and develop robust data pipelines using Informatica (PowerCenter or IICS) to migrate data from disparate sources into Teradata and the Lakehouse environment.
- Performance Tuning: Optimize Teradata SQL and Informatica mappings for high-volume data processing and complex financial calculations.
- Data Governance: Ensure compliance with financial regulations by implementing data lineage, quality checks, and metadata management within the FSLDM framework.
- Stakeholder Collaboration: Work closely with Business Analysts and Data Scientists to translate financial business requirements into scalable technical schemas.
Technical Requirements
- Core Model: Expert-level knowledge of FSLDM (Financial Services Logical Data Model) is mandatory.
- Primary Database: Extensive experience with Teradata (Vantage, Architecture, Utilities like BTEQ, FastLoad, MultiLoad).
- Integration Tools: Advanced proficiency in Informatica (PowerCenter/Informatica Intelligent Cloud Services).
- Lakehouse Experience: Proven experience in building or maintaining Data Lakehouse architectures (combining the flexibility of data lakes with the performance of data warehouses).
- Domain Knowledge: Strong understanding of Banking/Financial Services domains (Risk, Finance, Regulatory Reporting, or Retail Banking).
