Kumo.AI
AI on the Modern Data Stack
Artificial Intelligence • Machine Learning • Modern Data Stack
11 - 50
Data Engineer
March 12
🔄 Hybrid – Bay Area
Kumo.AI
AI on the Modern Data Stack
Artificial Intelligence • Machine Learning • Modern Data Stack
11 - 50
Description
• Seeking intellectually curious and highly motivated Data Engineers to become foundational members of our Machine Learning and Data Platform team • Required Qualifications for Ideal candidate 4+ years of professional experience in SaaS/Enterprise companies • Strong experience with data ingestion and connectors • Experience in building end-to-end production-grade data solutions on AWS or GCP • Experience in building scalable ETL pipelines • Ability to plan effective data storage, security, sharing, and publishing within an organization • Experience in developing batch ingestion and data transformation routines using ETL tools • Familiarity with AWS services such as S3, Kinesis, EMR, Lambda, Athena, Glue, IAM, RDS • Proficiency in several programming languages (Python, Scala, Java) • Familiarity with orchestration tools such as Temporal, Airflow, Luigi, etc • Self-starter, motivated, with the ability to structure complex problems and develop solutions • Excellent communication skills and ability to explain data and analytics strengths and weaknesses to both technical and senior business stakeholders • Preferred Qualifications - good to have Deep familiarity with Spark and/or Hive • Understanding of different storage formats like Parquet, Avro, Arrow, and JSON and when to use each • Understanding of schema designs like normalization vs. denormalization • Proficiency in Kubernetes, and Terraform • Azure, ADF and/or Databricks skills • Experience with integrating, transforming, and consolidating data from various data systems into analytics solutions • Good understanding of databases, SQL, ETL tools/techniques, data profiling and modeling • Strong communications skills and client engagement
Requirements
• 4+ years of professional experience in SaaS/Enterprise companies • Strong experience with data ingestion and connectors • Experience in building end-to-end production-grade data solutions on AWS or GCP • Experience in building scalable ETL pipelines • Ability to plan effective data storage, security, sharing, and publishing within an organization • Experience in developing batch ingestion and data transformation routines using ETL tools • Familiarity with AWS services such as S3, Kinesis, EMR, Lambda, Athena, Glue, IAM, RDS • Proficiency in several programming languages (Python, Scala, Java) • Familiarity with orchestration tools such as Temporal, Airflow, Luigi, etc • Self-starter, motivated, with the ability to structure complex problems and develop solutions • Excellent communication skills and ability to explain data and analytics strengths and weaknesses to both technical and senior business stakeholders • Preferred Qualifications - good to have Deep familiarity with Spark and/or Hive • Understanding of different storage formats like Parquet, Avro, Arrow, and JSON and when to use each • Understanding of schema designs like normalization vs. denormalization • Proficiency in Kubernetes, and Terraform • Azure, ADF and/or Databricks skills • Experience with integrating, transforming, and consolidating data from various data systems into analytics solutions • Good understanding of databases, SQL, ETL tools/techniques, data profiling and modeling • Strong communications skills and client engagement
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