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

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)

What We Offer:

- Competitive salaries and comprehensive health benefits.

- Flexible work hours options.

- Career development and training opportunities.

- A supportive and inclusive work environment.

📌 Data Architect (India)
🏢 BCE Global Technology Centre
📍 India