Software Engineer - Data Infrastructure

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Requirements:

• 6+ years of experience designing and building distributed data infrastructure at scale.
• Strong expertise in batch and streaming data processing technologies such as Spark, Flink, Kafka, or Airflow/Dagster.
• A proven track record of impact-driven problem-solving in a fast-paced environment.
• A strong sense of engineering excellence, with a focus on high-quality, reliable, and performant systems.
• Excellent technical communication skills, with experience working across both technical and non-technical counterparts.
• The ability to navigate ambiguity, take ownership, and drive projects from inception to execution.
• Experience mentoring and supporting engineers, fostering a culture of learning and technical excellence.

Responsibilities:

• Design and build large-scale distributed data systems that power analytics, AI/ML, and business intelligence.
• Develop batch and streaming solutions to ensure data is reliable, efficient, and scalable across the company.
• Manage data ingestion, movement, and processing through core platforms like Snowflake, our ML Datalake, and real-time streaming systems.
• Improve data reliability, consistency, and performance, ensuring high-quality data for engineering, research, and business stakeholders.
• Collaborate with AI researchers, data scientists, product engineers, and business teams to understand data needs and build scalable solutions.
• Drive technical decisions and best practices for data ingestion, orchestration, processing, and storage.