Spark / Scala + AWS/ Snowflake (Remote)

Cloud front, Aurora, Athena, AWS EC2, Data Modelling Fundamentals, Data Warehousing, ETL Fundamentals, Glue, Lake Formation, Lambda, Modern Data Platform Fundamentals, PLSQL, Python, S3, Spark – Pyspark, SQL (Basic + Advanced), Step Functions, EBS /EFS

Secondary Skills

Java, Spark – Scala

Specialization

AWS Data EngineerIng Basic: Lead Data Engineer

Job requirements

Bachelor’s in Computer Science, Engineering, or related technical discipline or equivalent combination of training and experience

10+ years programming experience: building application frameworks, and back-end systems for high-volume pipelines using Go/Java/Python. Python/Java preferred.

10+ years’ experience building data frameworks, platforms and scaling them to large volume of data using message brokers. Kafka experience is must.

5+ years’ experience building streaming platform using Apache Kafka, Confluent Kafka, AWS Managed Kafka Service.

5+ years’ experience ingesting data from SQL Server/My SQL/Oracle using Change Data Capture, debezium, and Kafka Connect.

2 years’ experience using AWS Data Services: any combination of DMS, EMR, Glue, Athena, S3, CloudWatch, Lambda or IAM

1-year exp. with data architecture, ETL and processing of structured and unstructured data

2 years’ experience with DevOps tools (any combination of GitHub, TravisCI or Jira) and methodologies (Lean, Agile, Scrum, Test Driven Development)