Senior Data Engineer; Snowflake

Design and evolve data architectures that support analytics, machine learning, and data-driven products. You’ll build and optimize production pipelines, data models, and integrations, taking responsibility for data quality, reliability, security, and performance across the delivery lifecycle. The position is fully remote and described as a full-time engagement.

• Develop and maintain Python-based ETL processes and write efficient SQL for extracting and transforming data.
• Build and optimize large-scale pipelines and warehouse solutions using Databricks and Snowflake.
• Automate data delivery, validation, augmentation, and other processing workflows.
• Translate stakeholder needs into scalable data solutions and develop APIs that supply data models.
• Partner with AI and machine learning engineers to identify data sources, gaps, and dependencies when implementing features.
• Monitor and troubleshoot performance and data integrity; build scalable infrastructure using SQL and AWS data technologies, while following applicable data-handling rules.

• At least five years of professional experience delivering production-quality software.
• Strong computer science fundamentals, including databases, data structures, operating systems, networking, and object-oriented programming.
• Experience with Python, SQL, and relational and No
  
  SQL databases such as Postgres, Cassandra, or MongoDB.
• Strong experience with Databricks and Snowflake, plus a cloud platform such as AWS, GCP, or Azure.
• Experience with data processing or orchestration tools such as Spark or Airflow.
• Proven ability to work with large and unstructured datasets, use Git, and communicate effectively in English.

• Familiarity with graph data modeling or graph databases such as Neo4j.

• Equity participation
• paid time off
• an annual retreat
• a company-wide winter break
• education support
• optional in-person meetups
• individualized career roadmaps are listed.