A technology company based in Raleigh, NC, is looking for an AWS Data Engineer with over 10 years of experience in data engineering, specifically in data warehouse and data mesh implementations. The candidate should have at least 4 years of experience with the AWS tech stack, including PySpark and AWS Glue. Expertise in ETL processes, data modeling, and technologies like Kafka and Kinesis is essential. This is an excellent opportunity for someone looking to advance their career in a dynamic environment.
Qualifications
10+ years in data engineering with specialization in data warehouses.
4 years of experience with AWS technologies including Glue and EMR.
Hands-on skills in data modeling and performance optimization.
Skills
AWS tech stack proficiency
PySpark knowledge
Data modeling skills
ETL process expertise
Kafka and Kinesis streams
Tools
AWS Glue
Redshift
Airflow
SQL
Job description
AWS Data Engineer
Skill Matrix: Overall 10+ years of specialization in data engineering in data warehouse and data mesh implementations
Must have 4 years of relevant experience in AWS tech stack - Writing PySpark, AWS Glue scripting (ETL & Crawler), EMR, Datasync, DMS, SQL, Redshift
Possesses experience in technologies such change data capture(CDC), data quality, Kafka and Kinesis data streams, Airflow, Step Functions, and Lambda
Knowledge on table formats such as Iceberg and Delta tables
Has experience in metadata management building data catalog in alignment with business glossary
Has knowledge of data governance aspects such as data lineage, data quality. Should have built data validation frameworks to reconcile source and target data
Hands‑on expertise with data modelling, ETL pipelines, and performance optimization.
Solid background in Data Warehousing concepts (star/snowflake schema design, dimensional modelling, and reporting enablement)