Gormat is seeking a candidate who possesses and applies a comprehensive knowledge across key tasks and high impact assignments. The ideal candidate is able to plan and lead major technology assignments, evaluate performance results, and recommend major changes affecting short-term project growth and success. The candidate will function as a technical expert across multiple project assignments and may supervise others. Position Description - Develop, and maintain robust and scalable data pipelines for enterprise AI applications including defining appropriate data model concepts - Develop high-performance data parsers for extremely large and complex datasets - Implement and manage various database systems, including graph, SQL, NoSQL, and vector databases - Collaborate with AI/ML engineers and data scientists to understand data requirements and optimize data access and retrieval for AI models - Ensure data quality, integrity, and security across all data storage solutions - Support the deployment and maintenance of AI applications by providing expert data engineering capabilities - Familiarity with AI concepts in the context of data storage, access, and retrieval - Continuously optimize data infrastructure for performance, cost-efficiency, and scalability What Required Skills You'll Bring: - Bachelor's degree in a relevant technical field with 8 years of experience; Master's degree in a relevant technical field with 5 years of experience; 4 years additional experience will be considered in lieu of degree - Advanced proficiency in programming languages commonly used for data engineering (e.g., Python, Java, Scala) - Demonstrated expertise in designing, developing, and optimizing data pipelines for large-scale enterprise environments - Proven experience with corporate dataflows and developing data parsers for extremely large datasets - Extensive experience with various database technologies including graph databases (e.g., Neo4j), SQL databases (e.g., PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, Cassandra), and vector databases - Familiarity with cloud platforms (AWS, Microsoft Azure) for data storage and processing What Desired Skills You'll Bring: - Experience with data governance, data security, and compliance best practices - Familiarity with big data technologies such as Hadoop, Spark, or Kafka. - Experience with data warehousing concepts and tools - Continuous learning mindset to stay abreast of cutting-edge data engineering and AI advancements - Understanding of machine learning concepts and their implications for data infrastructure - Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams - Ability to translate complex data requirements into actionable engineering solutions TS/SCI with CI polygraph is required.
Required skills
- Advanced proficiency in programming languages commonly used for data engineering (e.g.
- Python
- Java
- Scala)
- Demonstrated expertise in designing
- developing
- and optimizing data pipelines for large-scale enterprise environments
- Proven experience with corporate dataflows and developing data parsers for extremely large datasets Extensive experience with various database technologies including graph databases (e.g.
- Neo4j)
- SQL databases (e.g.
- PostgreSQL
- MySQL)
- NoSQL databases (e.g.
- MongoDB
- Cassandra)
- and vector databases Familiarity with cloud platforms (AWS
- Microsoft Azure) for data storage and processing.