10 years
0 Lacs
Posted:1 day ago|
Platform:
Remote
Contractual
Aventis Technology operates at the intersection of management consulting and custom IT services. We collaborate with innovative organizations to achieve strategic business objectives through the smart application of technology. Our approach integrates business insight and technical expertise, enabling us to transform challenges into opportunities for growth, efficiency, and a competitive edge.
Location: Remote Experience Level: 10+ years in Data Architecture and Data Platform Design Department: Data & AI Engineering
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.
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).
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).
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.
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.
Required Skills & Expertise
Area Expertise
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
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.
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.
Data architecture blueprint and documentation.
Customer & Offer 360 data model (batch + real-time).
Standardized data integration layer and APIs.
Feature store design for ML models.
Scalable orchestration and data quality framework. C
ost-optimized infrastructure setup and monitoring dashboards.
Reduction in data latency and processing time.
High data accuracy (>99%) and reliability across modules.
Cost per million records processed.
Data pipeline uptime and throughput.
Time to deploy new data sources or attributes
Please reach out vamsi@aventistechnology.com.ph or osman@aventistechnology.com.ph
Aventis Technology
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