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Data Engineer II
Netomi
Contract type
Ongoing
Work mode
100% remote
Experience
Mid-level · 4+ years
Job description
Key details
- Architect and implement scalable, secure, and reliable data pipelines using modern data platforms (e.g., Spark, Databricks, Airflow, Snowflake)
- 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
- Write clean, maintainable code with comprehensive unit and integration tests to ensure reliability and stability in Python
- Thrive in an agile, collaborative environment and take ownership of end-to-end feature delivery
- Company mission
- Information not specified
Primary stack
Core technologies
Python (Programming Language)DockerSQLKubernetes
Benefits
- Information not specified
Requirements & details
- 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
- 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
- Python, SQL, Apache Spark, Databricks, Apache Airflow, Snowflake, Apache Kafka, RabbitMQ, AWS Redshift, GCP BigQuery, Docker, Kubernetes, LLMs
- Python (Programming Language)
- Docker
- SQL
- Kubernetes