Data Software Engineer

What your day could consist of:

• Architect and Build Pipelines by designing, developing, and maintaining high-throughput data pipelines that seamlessly transform data across our ecosystem
• Execute Data Modeling and Schema Design, utilizing DDL and DML operations to optimize data structures for both performance and long-term scalability
• Champion Engineering Excellence by implementing automated testing, CI/CD pipelines, and Infrastructure as Code (Terraform) to ensure system health and reliability.
• Collaborate Cross-Functionally with Data Science and AI teams to engineer feature stores and automated MLOps pipelines, moving cutting-edge research into live production environments
• Drive System Monitoring and health checks, ensuring our containerized and orchestrated environments (Kubernetes, Docker, Airflow) run at peak efficiency.
• Act as a Technical Advisor to stakeholders, translating complex data architectures into clear, non-technical conversations that guide business decisions

Technical environment:

• Databases: MySQL, Amazon Aurora, Amazon RDS, PostgreSQL
• ata Storage and Analytics: AWS S3, Apache Iceberg, Snowflake, Apache Druid, Looker
• Data Processing and Transformation: Apache Spark, DBT
• Languages: Python (primary)
• Infrastructure as Code: Terraform
• Containerization and Orchestration: Kubernetes, Docker, Airflow

The Ideal Candidate Will Bring:

• 4+ years of professional software engineering experience, with a proven track record of building and maintaining production-grade data systems.
• Deep Data Architecture expertise, with the ability to design modern data stack components and schemas that balance immediate performance with future growth.
• Proficiency in Infrastructure as Code, specifically using Terraform to manage and deploy your own infrastructure.
• A high level of software rigor, including a strong background in automated testing, CI/CD, and general software engineering best practices
• Expert-level SQL skills (particularly MySQL), with a focus on optimizing complex queries for maximum performance.
• Experience in a modern technical environment, ideally having worked with Python, AWS (S3, Aurora, RDS), Snowflake, Apache Spark, and DBT
• Exceptional communication skills, with the talent to distill complex technical concepts into clear, actionable insights for both technical and non-technical peers