Design and architect scalable data platforms, data pipelines, and data engineering solutions.
Define and implement batch processing frameworks using Spring Batch and other relevant technologies.
Design data ingestion, transformation, processing, and storage patterns.
Drive data integration using Kafka, Google Pub/Sub, APIs, and event-based integrations.
Ensure data quality, consistency, validation, lineage, and traceability.
Define failure handling, recovery, and monitoring strategies for data pipelines.
Drive automation using Python and Bash scripting and optimize pipeline performance and scalability.
Lead the Data Engineering POD and drive architecture decisions, design reviews, and technical best practices.
Collaborate with Data, Platform, Product, and other technology teams to deliver solutions.
Mentor engineers and support the development of strong data engineering capabilities.
Remove technical blockers and ensure smooth delivery of POD activities.
Design and deploy GCP resources using Infrastructure as Code (IaC).
Support architecture governance, technical planning, and delivery milestones.

Strong experience in Data Engineering Architecture, solution design, and data platform development.
Hands-on experience with GCP / Google Cloud Platform and cloud-based data solutions.
Strong proficiency in Python for data engineering and automation.
Hands-on experience with Data Pipelines, ETL, and Data Integration.
Experience with Spring Batch, Kafka, and Google Pub/Sub.
Good understanding of Data Quality, Data Governance, and data management principles.
Experience with Infrastructure as Code (IaC) and tools such as Terraform.
Strong knowledge of data formats including Avro, JSON, and Parquet.
Experience with API Integration, Event-Driven Architecture, and Batch Processing.
Good knowledge of Bash Scripting and cloud-based development practices.
Strong Technical Leadership / POD Leadership experience with excellent stakeholder management

Architect / POD Lead – Data Engineering

Let the right jobs find you