Senior Data Engineer

Responsibilities

• Design and implement robust, cloud-based data storage solutions, optimizing schemas for multi-tenant environments while ensuring data accessibility and security and a high standard of trust and transparency
• Develop, deploy, and maintain resilient ETL/ELT pipelines for both real-time streaming and batch processing, ensuring seamless data flow from raw ingestion to production-ready applications
• Build and manage data access layers, including REST APIs and streaming services, to empower downstream users
• Drive data governance and best practices: Contribute across teams to recommend tools, processes, and best practices for maintaining data health, integrity, and security
• Support AI operations (MLOps) by managing versioning, containerization, and deployment of AI models
• Build monitoring and alerting systems to track data health and system performance, proactively identifying and remediating bottlenecks

Qualifications

• Bachelor’s degree or higher in Computer Science, Engineering, or Data Science
• 5+ years of professional experience in data engineering or a related role
• A strong foundation in Python (or equivalent), including testing frameworks (e.g., pytest) and ORMs (e.g., SQLAlchemy)
• You understand modularity and how to define clear scopes and responsibilities within a large codebase
• Proven experience architecting scalable relational and non-relational (SQL/noSQL) schemas
• You manage the end-to-end database lifecycle, from initial design to production maintenance
• Expertise in maximizing system performance through advanced query tuning, strategic indexing, and execution plan analysis to eliminate technical bottlenecks
• Experience with one or more cloud-based databases (e.g., AWS RDS, Azure Database)
• You are comfortable configuring compute resources, backups, and geolocation requirements
• Experience building resilient pipelines using frameworks such as Dagster or Apache Airflow
• You have a track record of maintaining data health for both real-time streaming and batch processing
• A strong understanding of how data infrastructure integrates into the broader application architecture
• Experience with modern software development practices, including version control (Git), CI/CD pipelines, and a commitment to high-quality, maintainable code

Preferred Qualifications

• Experience working with streaming data (e.g., Kafka) or running data models on the edge (e.g., Raspberry Pi, IoT devices)
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes
• Experience architecting and consuming scalable RESTful APIs using standardized design principles and robust authentication protocols
• Familiarity with blockchain data indexing or privacy-preserving data processing techniques
• Experience mentoring junior engineers or leading technical projects within a high-performing team

What does it take to be a successful VIAneer? Let’s break it down, VIAneers are

• Self-motivated and passionate about leaving everything they touch better than how they found it
• Firm believers that people should love what they do and are eager to build a culture that enables them to do their best work
• Creative problem solvers who respectfully challenge the status quo in the pursuit of excellence
• People who lead discussions with curiosity and value diverse perspectives…