Staff Software Engineer- Data Infrastructure

Aledade - Austin, TX

Full-time - Senior

Austin, TX

Professional, Scientific, and Technical Services

About the position

As a Staff Software Engineer, you will lead the development of next-generation distributed data storage and processing systems, moving beyond traditional monolithic SQL engines and batch pipelines. This role focuses on building scalable systems that enhance query performance while providing simple and expressive interfaces for various data consumers, including web applications, business analytics, and artificial intelligence.

Responsibilities

• Identify and develop scalable and performant solutions.
• Work across disciplines to shape product strategy and execution.
• Develop the foundations of code architecture and quality.
• Mentor and coach engineers.
• Set and uphold the standard for engineering processes to support high-quality engineering.

Requirements

• BS/BTech (or higher) in Computer Science, Engineering or a related field required.
• 8+ years of production-level experience as an engineer building highly scalable systems.
• 4+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value.
• 4+ years of experience working with SQL or other database querying languages on large multi-table data sets.
• Experience architecting, developing, and deploying large-scale distributed systems at scale.
• Experience with cloud technologies, e.g., AWS, Azure, GCP.
• Experience building continuous integration and continuous development (CI/CD) pipelines.
• Strong familiarity with server-side web technologies (e.g., Java, Python, Scala, C#, C++, Go).

Nice-to-haves

• Working knowledge of health-tech systems, like Electronic Health Records, Clinical data, etc.
• 8+ years of production-level experience as an engineer building highly scalable and reliable infrastructure.
• Experience in designing, building and optimizing data pipelines and ETL processes.
• Proficiency in working with large datasets and knowledge of data storage technologies.
• Experience working with data ingestion systems and optimizing performance for handling large-scale data processing and analysis.
• In-depth knowledge of database systems.
• Familiarity with database replication, sharding and other techniques for scalability and high availability of databases.
• Experience in performance monitoring and optimization of data systems and infrastructure.
• Experience with containerization and orchestration technologies such as Docker and Kubernetes.