Senior Software Engineer

Amazon•Seattle, WA

43d

About The Position

IVS is building the future of interactive video and we are seeking a Data Infrastructure Engineer to design, build, and maintain the systems that power our data-driven organization. In this role, you will ensure that our data pipelines, storage, and processing systems are reliable, scalable, and optimized for analytics, machine learning, and business intelligence use cases. You will collaborate with data engineers, analysts, and software teams to create infrastructure that enables efficient and secure access to high-quality data.

Requirements

5+ years of non-internship professional software development experience
5+ years of programming with at least one software programming language experience
5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
Experience as a mentor, tech lead or leading an engineering team
6+ years of experience in data engineering, DevOps, or infrastructure engineering roles.
Strong hands-on expertise with cloud platforms
Proficiency in data pipeline tools (e.g., Airflow, dbt, AWS Glue, Flink).
Experience with data storage technologies (e.g., Redshift, Snowflake, BigQuery, Delta Lake, Iceberg, Parquet).
Proficiency in GO, SQL, and Python for building and maintaining data systems.
Solid understanding of distributed systems and performance optimization.

Nice To Haves

Experience with real-time data streaming and event-driven architectures.
Strong hands-on expertise with AWS cloud
Background in observability and monitoring
Knowledge of data governance, security, and compliance best practices
Prior experience supporting machine learning or advanced analytics environments.

Responsibilities

Design, implement, and maintain scalable data infrastructure in AWS cloud
Build and optimize data pipelines (batch and streaming) to support analytics, reporting, and ML workloads.
Ensure data quality, reliability, and observability through monitoring, logging, and automated alerting.
Work closely with data engineering and analytics teams to understand requirements and deliver high-performance solutions.
Champion best practices for security, compliance, and governance in data infrastructure.
Identify opportunities to optimize performance and cost of data platforms.
Stay current with emerging tools, frameworks, and cloud services in the data infrastructure ecosystem.