Data Architect

Key Responsibilities:

Data Engineering Architecture (Primary)

• Design and build scalable data platforms, pipelines, and architectures
  
• Define batch and streaming frameworks (Kafka, Pub/Sub, OpenShift/Kubernetes, GitLab CI/CD, ArgoCD, Optional - Spring Batch)
  
• Establish data ingestion, transformation, and storage patterns
  
• Design event-driven and real-time data solutions
  

Data Processing & Integration

• Build real-time data pipelines and streaming integrations
  
• Standardize data formats (Avro, JSON, Parquet) and connectors
  
• Enable API-driven (optional) and event-based system integrations
  
• Batch Processing, MongoDB, Redis, Helm Charts, Kibana /Elasticsearch, Artifactory
  

Data Quality & Governance

• Ensure data quality, consistency, and reliability
  
• Implement data validation, lineage, and traceability
  
• Define failure handling and recovery strategies
  

Automation & Optimization

• Drive automation using Python / Bash scripting
  
• Continuously improve pipeline performance and scalability
  
• GCS , Ingress / API Gateways, Enterprise Platform Services
  

Requirements

Required Skills:

• POD Leadership - Act as technical lead for the POD
  
• Drive architecture decisions, design reviews, and best practices
  
• Collaborate with data, platform, and product teams
  
• Mentor engineers and build data engineering capability
  
• Ensure smooth work progression (To Do → In Progress → Done) and remove blockers
  
• Streaming is of lower priority as we are migrating out of real-time for our monetization platforms.
  
• Deploy data engineering GCP resources as code (IaaC)
  

Benefits

What We Offer:

• Competitive salaries and comprehensive health benefits.
  
• Flexible work hours options.
  
• Professional development and training opportunities.
  
• A supportive and inclusive work environment.