ExperienceLevel: 5-6 years in Data Engineering withmanagerial experience
JobDescription: We are seeking an experienced Senior DataEngineer with a strong technical background and management expertise to overseethe development and optimization of our data infrastructure. The idealcandidate will be adept in designing robust data pipelines, managingcloud-based data systems, and leading a team of skilled data professionals tosupport our AI-driven mission planning and strategic decision support systems.
Data Architecture: Design and implement comprehensive data strategies for strategic and operational data integration.
Machine Learning Support: Build and maintain infrastructure to support the lifecycle of machine learning models.
Data Governance: Ensure data quality and integrity across all pipelines and platforms.
Real-time Data Processing: Develop systems for real-time data analysis to support mission-critical decisions.
Collaboration and Leadership: Guide and collaborate with cross-functional teams to align data engineering efforts with business goals.
Vectorized Data Management: Spearhead the management of vector databases, optimizing data for ML applications.
API and Integration: Architect and develop APIs for efficient data exchange and integration with various applications.
Cloud Infrastructure: Oversee the management of cloud environments to ensure scalable and resilient data operations.
Performance Optimization: Monitor and enhance the efficiency of data workflows and vector database solutions.
Stakeholder Communication: Provide clear and concise project updates to stakeholders, articulating project status, challenges, and next steps.
Cloud Computing: Proficient in managing data on cloud platforms like AWS, GCP, or Azure.
Database Mastery: Expertise in both SQL and NoSQL databases such as MySQL, MongoDB, and SQL Server.
Data Pipeline Engineering: Demonstrated experience in constructing and maintaining reliable data pipelines.
Programming Proficiency: Skilled in Python, Java, SQL, and JSON for data-related tasks.
Data Modeling: Ability to perform query optimization and data modeling for efficient data access.
Machine Learning Familiarity: Understanding of ML frameworks to support data science teams.