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, DecisionRules.io, 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, YAML
* API & Integration Design-REST, GraphQL, Kafka Connect, JSON schema
* Security & Compliance-IAM, encryption (KMS), access control, masking, PDPA compliance
Preferred (Nice-to-Have)
* Telecom industry experience (recharge, balance, offer, churn, usage data).
* Experience integrating with Adobe Experience Platform (AEP) or Pricefx.
* Knowledge of DecisionRules.io, KNIME, or n8n for workflow orchestration.
* Familiarity with AI/ML pipelines and MLOps frameworks (MLflow, SageMaker).
* Exposure to knowledge graphs (Neo4j, GraphFrames) for segmentation and recommendation.
* Educational Background Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related fields.
* Certifications in AWS/Azure Data Architect, Databricks Certified Data Engineer, or Snowflake Architect are preferred.