What are the responsibilities and job description for the Data Architect position at Recfront?
Role: Data Architect
About Our Client
Our client is a global enterprise building and operationalizing advanced data and AI solutions for large organizations across industries. They work at the intersection of data engineering, analytics, and artificial intelligence, enabling enterprises to convert complex data ecosystems into structured, AI-ready assets that drive measurable outcomes.
With a global delivery footprint across 30 countries and a large team of data and technology professionals, they serve enterprise clients across North America, Europe, and Asia-Pacific, delivering capabilities in data engineering, cloud transformation, analytics, and AI enablement.
Job Overview
As a Data Architect, you will design scalable, high-performance data ecosystems that transform raw data into AI-ready structures.
You will define enterprise data models and architecture frameworks supporting advanced analytics, predictive modeling, and Generative AI use cases. The role requires strong technical leadership to bridge business needs with engineering execution.
Key Responsibilities
Architecture & Design
- Define end-to-end data architecture aligned with analytics and AI strategy
- Design conceptual, logical, and physical data models for enterprise-scale systems
- Optimize data structures for analytics, reporting, and AI workloads
Data Platform Design
- Build Lakehouse architecture using Bronze, Silver, and Gold layers
- Ensure data quality, lineage, and transformation governance
Governance & Standards
- Define data standards including metadata, security, and MDM
- Support enterprise data governance and compliance needs
AI Enablement
- Collaborate with Data Science teams on LLM-ready data structures
- Support Vector databases and RAG-based architecture designs
Stakeholder Management
- Work with engineers, analysts, and business teams
- Translate business requirements into scalable technical designs
Technical Expertise
Experience
- 8 years in Data Architecture or Senior Data Engineering roles
Data Modeling
- 3NF, Dimensional Modeling (Star/Snowflake), Data Vault 2.0
Reverse Engineering
- Experience modernizing legacy data systems
Tools
- ER/Studio, Erwin Data Modeler, Lucidchart
Cloud & Big Data
- Azure (Fabric/Synapse), AWS (Redshift/Glue), Snowflake
- Spark and Delta Lake experience
Data Systems
- Strong SQL (PostgreSQL, SQL Server)
- NoSQL databases
- Exposure to Vector databases (Pinecone, Milvus)