netomi - Backend Engineer II – Data Platform
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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 Spring Boot ecosystem. • Solid understanding of Relational Databases (RDS, MySQL, PostgreSQL). • Experience with Apache Kafka or RabbitMQ for building asynchronous, decoupled systems. • Proficiency with Python, SQL, and at least one data pipeline orchestration tool (e.g., Apache Airflow, Luigi, Prefect). • Strong experience with cloud-based data platforms (e.g., AWS Redshift, GCP BigQuery, Snowflake, Databricks). • Deep understanding of data modeling, data warehousing, and distributed systems. • Familiarity with DevOps practices (CI/CD, infrastructure as code, 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 (e.g., GDPR, HIPAA). • Familiarity with prompt engineering and how LLM-based systems interact with data.
Responsibilities
• Architect and implement clean, modular, and scalable backend services using Java, Spring Boot, and modern microservice principles. • Design efficient database schemas and write optimized queries for RDS (MySQL/PostgreSQL) and, optionally, NoSQL databases like Elasticsearch, MongoDB, or DynamoDB. • Integrate Kafka or RabbitMQ to build robust and loosely-coupled event-driven architectures. • Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., Spark, Databricks, Airflow, Snowflake, etc.). • Develop ETL/ELT processes to ingest data from various structured and unstructured sources. • Perform Exploratory Data Analysis (EDA) to uncover trends, validate data integrity, and derive insights that inform data product development and business decisions. • Collaborate closely with data scientists, analysts, and software engineers to design data models that support high-quality 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 to ensure reliability and stability. • Thrive in an agile, collaborative environment and take ownership of end-to-end feature delivery.
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