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Backend Engineer II – Data Platform

3 hours, 52 minutes ago
India
Full-time
Mid Level
Backend Engineer
Software Development
Agile Apache Airflow Apache Spark CI/CD Databricks Docker DynamoDB Elasticsearch HIPAA Java Kafka Kubernetes Luigi Microservices MongoDB MySQL PostgreSQL Prefect Python RabbitMQ Snowflake Spring Boot SQL
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Netomi

Netomi

Netomi is an AI-first customer service platform revolutionizing customer support with industry-leading resolution rates and multilingual support.

IT Services
51-250
Founded 2015
$52M raised
View All Jobs 34

Description

  • Architect and implement clean, modular, and scalable backend services using Java and Spring Boot.
  • Design efficient database schemas and write optimized queries for relational databases and optionally NoSQL databases.
  • Integrate Kafka or RabbitMQ to build robust event-driven architectures.
  • Architect and implement scalable, secure, and reliable data pipelines using modern data platforms.
  • Develop ETL and ELT processes to ingest data from structured and unstructured sources.
  • Perform exploratory data analysis to uncover trends, validate data integrity, and derive insights.
  • Collaborate with data scientists, analysts, and software engineers to design data models for analytics and real-time insights.
  • Profile and tune backend performance across databases, APIs, and infrastructure.
  • Write clean, maintainable code with comprehensive unit and integration tests.
  • Take ownership of end-to-end feature delivery in an agile, collaborative environment.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 4+ years of hands-on experience in data engineering or backend software development roles.
  • Strong expertise in Java and the Spring Boot ecosystem.
  • Solid understanding of relational databases such as MySQL and PostgreSQL.
  • Experience with Apache Kafka or RabbitMQ for asynchronous, decoupled systems.
  • Proficiency with Python, SQL, and at least one data pipeline orchestration tool such as Apache Airflow, Luigi, or Prefect.
  • Strong experience with cloud-based data platforms such as AWS Redshift, GCP BigQuery, Snowflake, or Databricks.
  • Deep understanding of data modeling, data warehousing, and distributed systems.
  • Familiarity with DevOps practices, including CI/CD, infrastructure as code, and containerization with Docker/Kubernetes.
  • Exposure to AI/ML-integrated solutions or interest in working alongside data science teams.
  • Knowledge of data security and privacy regulations such as GDPR or HIPAA.
  • Familiarity with prompt engineering and how LLM-based systems interact with data.

Interested in this position?

Apply directly on the company website

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