Product Platform Engineer

Experion Technologies; Ernakulam; Presencial; INR 1.200.000 - 2.400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Flexible work arrangements

Descripción de la vacante

Experion Technologies Pvt. Ltd. is seeking a Product Platform Engineer with 4–7 years of software engineering experience to design and build cloud-native platform components on AWS and Azure, focusing on scalable data pipelines and event-driven architectures.

You will work with Spark, Flink, Kafka/MSK, and NoSQL data stores to implement Medallion Architecture, CI/CD automation, and secure, observable services across cloud environments.

Formación

• 4-7 years of professional software engineering experience.
• Hands-on with Spark and Flink for distributed batch and real-time streaming.
• Strong understanding of Kafka/MSK topics, partitions, producers/consumers.
• Experience with AWS and Azure cloud services (S3, Blob storage).
• Understanding of Medallion Architecture (Bronze/Silver/Gold).
• Experience with NoSQL databases and star-schema modelling.
• Knowledge of event-driven architectures, API design, and distributed systems.

Responsabilidades

• Design, develop, and maintain cloud-native platform components across AWS and Azure.
• Build event-driven ingestion and processing pipelines using MSK/Kafka, Flink, Spark or AWS Glue.
• Move data reliably across streaming, processing, and cloud storage layers (S3/Azure Blob).
• Containerize services with Docker and support deployment to managed container platforms.
• Design microservices with clear boundaries, asynchronous comms, resilience, and observability.
• Apply Medallion Architecture across bronze, silver, and gold data layers.
• Use NoSQL databases appropriately and support analytical models with star-schema patterns.
• Adhere to ISMS policies; integrate AI/ML services via secure, governed interfaces.
• Collaborate with application, data, infra, security, and AI/ML teams to deliver reusable platform capabilities.
• Follow API-first and event-driven design; ensure idempotency, retries, DLQ, and replayability.
• Practice IaC and CI/CD; Terraform/CloudFormation/Bicep exposure is desirable.
• Follow cloud security fundamentals: IAM, secrets, encryption, network controls, least privilege.
• Maintain observability via structured logging, metrics, tracing, dashboards, and alerts.
• Conduct unit, integration, contract, and performance testing for cloud/distributed workloads.
• Create design-decision records, runbooks, and architectural diagrams.

Conocimientos

Apache Spark

Apache Flink

Apache Kafka

Amazon MSK

AWS

Azure

Docker

NoSQL databases

microservices

REST APIs

Observability

Data architecture

S3

Azure Blob

Medallion Architecture

Cloud storage

Herramientas

Terraform

CloudFormation

Kubernetes

Descripción del empleo

Skills -Apache Spark, Apache Flink, Apache Kafka / Amazon MSK, AWS and Azure cloud platforms, distributed data processing, data architecture, Docker, cloud storage (AWS S3 / Azure Blob), NoSQL databases, microservices, REST APIs, event-driven architecture, observability

Job Description -

• 4-7 years of professional software engineering experience
• Hands-on experience with Apache Spark and Apache Flink for distributed batch and real-time stream processing.
• Strong understanding of Apache Kafka / Amazon MSK, including topics, partitions, producers, consumers, consumer groups, retries and failure handling.
• Practical exposure to AWS and Azure cloud services, including AWS S3, Azure Blob Storage and cloud-based data integration.
• Understanding of data architecture patterns, including Medallion Architecture (Bronze, Silver and Gold layers).
• Experience with NoSQL databases and analytical data modelling concepts, including star-schema modelling.
• Understanding of event-driven architectures, asynchronous communication, API design and distributed systems.

As a Product Platform Engineer, you will:

• Design, develop, and maintain cloud-native platform components across AWS and Azure.
• Build event-driven ingestion and processing pipelines using MSK/Kafka, Flink, Spark, or AWS Glue.
• Implement reliable data movement across streaming, processing, and cloud storage layers such as S3 and Azure Blob Storage.
• Containerize services using Docker and support deployment into managed container platforms.
• Design microservices with clear boundaries, asynchronous communication, resilience, security, observability, and production supportability.
• Apply Medallion Architecture patterns across bronze, silver, and gold data layers.
• Use NoSQL databases appropriately and support analytical models where starschema patterns are required.To adhere to ISMS policiesand procedures
• Integrate AI/ML or GenAI services into enterprise applications through secure, governed, and observable interfaces.
• Collaborate with application, data, infrastructure, security, and AI/ML teams to deliver reusable platform capabilities.
• API-first and event-driven design, including idempotency, retries, dead-letter handling, and replayability.
• Infrastructure as Code and automated CI/CD practices; Terraform, CloudFormation, Bicep, or equivalent exposure is desirable.
• Cloud security fundamentals: identity and access management, secrets management, encryption, network controls, and least privilege.
• Observability through structured logging, metrics, tracing, dashboards, and alerting.
• Unit, integration, contract, and performance testing for cloud and distributed workloads.
• Clear technical documentation, architecture diagrams, operational runbooks, and design-decision records.
• AWS Lambda, ECS/Fargate, IAM, CloudWatch, Step Functions, and API Gateway exposure.
• Experience with schema management, data quality, lineage, metadata, governance, or catalog services.
• Understanding of distributed-system trade-offs, performance tuning, cost optimization, and production incident troubleshooting.