Data Engineer

What You’ll Do 
●Design, build, and optimize high-performance data pipelines for large-scale time series data
●Implement scalable data infrastructure using tools such as KDB+, TimeSet (Google’s large time
series database), or Kronos
●Develop efficient data ingestion and transformation workflows that handle real-time and historical
time series data
●Connect time series data systems with Python-based model pipelines to support machine learning
training and inference
●Collaborate with data scientists and ML engineers to ensure data availability, quality, and
accessibility for experimentation and production
●Design data models and schemas optimized for time series use cases, including downsampling,
aggregation, and indexing strategies
●Ensure system reliability, scalability, and performance through monitoring, testing, and tuning
●Establish data governance, lineage, and observability best practices in large-scale environments
●Mentor junior engineers on large-scale data design, distributed processing, and real-time system
architecture
●Partner with product, engineering, and infrastructure teams to align data systems with business
goals