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

Eager to explore new ideas, understand the power of feedback, and constantly seek opportunities to grow and develop their skills

Strong team players who thrive in collaborative environments and celebrate the success of others