Why This Role Stands Out
This hybrid role offers a significant opportunity to leverage your advanced data engineering expertise on impactful projects, contributing to enterprise AI applications within a reputable company. You'll thrive here if you're a seasoned data professional with a strong background in large-scale data pipelines and diverse database technologies, ready to embrace technical leadership and continuous learning. Apply now to join a dynamic team and advance your career!
Quick Overview
Job Description
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 polygraph is required.
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