Data Engineer
About The Position
Designs, implements, and optimizes end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data. Develops robust ETL processes to integrate data from diverse sources into the data ecosystem. Designs and maintains data models, schemas, and database structures to support analytical and operational use cases. Optimizes data storage and retrieval mechanisms for performance and scalability. Evaluates and implements data storage solutions including relational databases, NoSQL databases, data lakes, and cloud storage services. Builds and maintains integrations with internal and external data sources and APIs. Implements RESTful APIs and web services for data access and consumption. Configures and manages data infrastructure components including databases, data warehouses, data lakes, and distributed computing frameworks. Monitors system performance, troubleshoots issues, and implements optimizations to enhance reliability and efficiency. Creates visual management standards to communicate performance.
Requirements
- Must be a U.S. Person (as defined by ITAR).
- Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
- 5+ years of experience in data engineering, software development, or related roles.
- Proficiency in programming languages commonly used in data engineering (e.g., Python, Java, Scala).
- Strong knowledge of database systems, data modeling techniques, and SQL proficiency.
- Proficiency with ETL tools commonly used in data engineering.
- Experience with big data technologies and frameworks.
- Familiarity with cloud platforms and services (e.g., AWS).
- Experience implementing RESTful APIs and web services for data access and consumption.
- Ability to lift up to 35 pounds, approximately 20% of a standard workday, and available for international travel 25% of the time.
Responsibilities
- Designs, implements, and optimizes end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
- Develops robust ETL processes to integrate data from diverse sources into the data ecosystem.
- Designs and maintains data models, schemas, and database structures to support analytical and operational use cases.
- Optimizes data storage and retrieval mechanisms for performance and scalability.
- Evaluates and implements data storage solutions including relational databases, NoSQL databases, data lakes, and cloud storage services.
- Builds and maintains integrations with internal and external data sources and APIs.
- Implements RESTful APIs and web services for data access and consumption.
- Configures and manages data infrastructure components including databases, data warehouses, data lakes, and distributed computing frameworks.
- Monitors system performance, troubleshoots issues, and implements optimizations to enhance reliability and efficiency.
- Creates visual management standards to communicate performance.
Benefits
- Medical, dental, and vision (Cigna)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
