Data Architect – Dynamic Pricing & Decision Intelligence Platform

At TechBiz Global , we are providing recruitment service to our TOP clients from our portfolio. We are currently seeking an Data Architect to join one of our clients ' teams. If you're looking for an exciting opportunity to grow in a innovative environment, this could be the perfect fit for you. Role Summary: The Data Architect will design and govern the complete data ecosystem for the ValueX platform — including data ingestion, processing, modeling, storage, orchestration, and governance. They will define the data architecture blueprint supporting the system’s core modules. 1. Customer Segmentation 2. Business Decisioning & Offer Assignment Engine 3. Real-Time Offer Orchestration Module (ROOM) 4. ML/AI Model Management & Simulation Engine The architect will ensure scalability to handle 50 million+ customer profiles, real-time event streams, and ML-driven decisioning — with a focus on performance, cost optimization, and maintainability. Key Responsibilities: Data Architecture & Design - Define the end-to-end data architecture across batch, streaming, and real-time layers. - Design Customer 360 and Offer 360 data models, including feature store and historical layers. - Establish logical, physical, and semantic data models to enable segmentation, scoring, and orchestration. - Define data contracts for Kafka topics, API payloads, and Adobe/CDP integrations. - Set up data versioning and lineage frameworks to track data provenance Data Ingestion & Integration - Architect data ingestion pipelines from multiple telco sources: OCS, CRM, Kenan, Billing, DWH, Adobe AEP, Pricefx, and external APIs. - Define patterns for real-time event ingestion (recharge, offer purchase, balance check). - Standardize data access through APIs or data products for downstream modules. - Design connectors for cloud storage (e.g., S3, Delta Lake) and integration middleware (e.g., n8n, , KNIME). Data Management & Governance - Define and enforce data quality, lineage, catalog, and access policies. - Establish metadata management frameworks (e.g., DataHub, Collibra, Amundsen). - Set up data validation and DQ frameworks (Great Expectations, Deequ). - Govern data partitioning, schema evolution, retention, and archiving strategies. - Ensure compliance with data privacy and regulatory standards (e.g., PDPA, GDPR, local telecom data policies). Scalability, Cost & Performance - Design for high performance and cost-efficient scalability (25M → 50M → 75M customers). - Optimize compute/storage balance across environments (Dev, UAT, Prod). - Define data lakehouse optimization strategies (Z-Order, Delta caching, compaction). - Monitor and manage query performance, cluster sizing, and job orchestration costs. Collaboration & Governance - Work closely with Data Engineers, Data Scientists, and Application Developers to ensure architectural alignment. - Lead architecture review boards and maintain data design documentation (ERD, flow diagrams, schema registry). - Serve as technical liaison between business stakeholders, data teams, and platform vendors (Databricks, Adobe, Pricefx). - Provide best practices and design patterns for model deployment, retraining, and data lifecycle management. Requirements - 10+ years in Data Architecture and Data Platform Design - Data Architecture-Data lakehouse design, data modeling (dimensional, normalized, semantic), schema management. - ETL/ELT & Orchestration-Databricks, Snowflake, dbt, Airflow, AWS Glue, Azure Data Factory. - Streaming & Real-Time-Apache Kafka, Spark Streaming, Kinesis, Flink - Data Modeling-Customer 360, Offer 360, Transaction 360, Feature Store - Cloud Platforms-AWS (S3, Glue, Lambda, EMR), Azure (ADF, Synapse), or GCP (BigQuery, Dataflow) - Storage & Compute-Delta Lake, Parquet, Iceberg, Snowflake - Data Quality & Governance-Great Expectations, Deequ, DataHub, Collibra - Programming & Scripting-Python, SQL, PySpark