Lead AWS Data Engineer
FUSTIS LLC
Senior AWS Data Engineer Must Have PySpark ramp-up Glue job hands-on proof Dimensional modeling Core Responsibilities Develop and maintain PySpark-based ETL pipelines for batch and incremental data processing Build and operate AWS Glue Spark jobs (batch and event-driven), including: Job configuration, scaling, retries, and cost optimization Glue Catalog and schema management Design and maintain event-driven data workflows triggered by S3, EventBridge, or streaming sources Load and transform data into Amazon Redshift, optimizing for: Distribution and sort keys Incremental loads and upserts Query performance and concurrency Design and implement dimensional data models (star/snowflake schemas), including: Fact and dimension tables Slowly Changing Dimensions (SCDs) Grain definition and data quality controls Collaborate with analytics and reporting teams to ensure the warehouse is BI-ready Monitor, troubleshoot, and optimize data pipelines for reliability and performance Required Technical Experience Strong PySpark experience (Spark SQL, DataFrames, performance tuning) Hands-on experience with AWS Glue (Spark jobs, not just crawlers) Experience loading and optimizing data in Amazon Redshift Proven experience designing dimensional data warehouse schemas Familiarity with AWS-native data services (S3, IAM, CloudWatch) Production ownership mindset (debugging, failures, reprocessing) Skills SPARK SQL
DATA SERVICES
MODELING
PYSPARK
AWS #J-18808-Ljbffr FUSTIS LLCVacancy posted 4 days ago
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