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Senior Data Engineer

Benjamin Leclerc

Full-time · Job · Los_Angeles

About the role

Every ML model is only as good as its data, and ours processes 800GB daily from IoT sensors deployed across 200 wind farms. Turbine vibration data, weather feeds, SCADA signals — all of it needs to arrive clean, on time, and in the right format for our predictive maintenance models to work. You'll own the streaming and batch data infrastructure: Kafka for real-time ingestion, Spark for transformation, Snowflake for the analytical layer, and Airflow for orchestration. The current pipeline works but doesn't scale — we're adding 50 new wind farms this year and need someone who can re-architect for 3x throughput. This is a senior role with real ownership. You'll make architectural decisions, set coding standards for the data team, and work directly with ML engineers to design feature stores that actually serve their needs.

Responsibilities

  • Re-architect streaming data pipelines to handle 3x throughput growth
  • Own Kafka-based real-time ingestion from IoT sensor networks
  • Design and optimize Snowflake schemas for ML feature stores
  • Build monitoring and data quality frameworks for mission-critical pipelines
  • Set technical standards and mentor two mid-level data engineers

Requirements

  • 5+ years in data engineering at scale
  • Deep experience with Kafka, Spark, and Snowflake
  • Strong Airflow skills for complex DAG orchestration
  • AWS expertise (S3, EMR, Kinesis, Glue)
  • Experience with IoT or time-series data preferred

Benefits

  • Fully remote — West Coast hours preferred
  • Senior equity package
  • $3,500 annual learning and conference budget
  • Impact on renewable energy infrastructure

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Categories

data science & analytics MLOps & AI Infrastructure

Skills

python spark kafka snowflake airflow

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Job Type

Full-time

Level

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Language

English

Salary Range

$160k – $200k / year

AI Expertise

data science & analytics MLOps & AI Infrastructure

Skills

python spark kafka snowflake airflow aws sql

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