Data Engineer - Onsite
MSYS Inc.
Wilmington, DE, United States
about 1 month ago
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Role details
Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Working hours
Regular working hours
Job source
Tech stack
Java (Programming Language)
Amazon Web Services
Amazon S3
Big Data
Cloud Computing
Cloud Engineering
Information Engineering
Data Infrastructure
Data Transformation
Distributed Computing Environment
Distributed Data Store
Distributed Systems
+20 more
Python (Programming Language)
Microsoft Message Queuing
Cloud Services
Data Processing
Data Ingestion
Snowflake
Apache Spark
Infrastructure as Code (IaC)
Event Driven Architecture
Pyspark
AWS Aurora
Apache Kafka
Data Management
Terraform
Stream Processing
Data Pipelines
AWS EKS
Amazon Elastic Mapreduce (EMR)
Service Stack
Databricks
Job description
We are seeking a highly skilled Data Engineer to join a team responsible for building and enhancing a large-scale decision platform that drives customer-focused business decisions. The ideal candidate will have strong expertise in Spark, Java, AWS, and large-scale data processing environments., * Design, develop, and optimize scalable data pipelines for ingesting and processing high-volume datasets.
- Build and maintain distributed data processing solutions using Apache Spark and Java.
- Process and manage 20M+ to 40M+ daily data records efficiently.
- Develop batch and real-time data processing workflows.
- Work with event-driven architectures and streaming platforms.
- Collaborate with cross-functional teams to enhance data platform capabilities.
- Implement and manage cloud-native solutions within AWS environments.
- Utilize Infrastructure as Code (IaC) methodologies using Terraform.
Requirements
- 5 to 10 years of experience.
- Strong experience with Apache Spark (Must Have)
- Strong experience with Java (Must Have)
- Hands-on experience with AWS Cloud Services (Must Have)
- Experience with Terraform for Infrastructure as Code (Must Have)
- Experience building data ingestion and data transformation pipelines
- Experience working with large-scale distributed data environments
- Knowledge of real-time and batch data processing architectures
Preferred skills:
- Python
- Apache Kafka
Cloud & Technology Stack:
- Apache Spark
- Java
- AWS EKS
- AWS EMR
- AWS S3
- AWS Aurora
- AWS MSK
- AWS SNS
- AWS SQS
- Apache Kafka
- Terraform, * Strong background in data engineering and distributed computing.
- Experience handling high-volume data platforms.
- Comfortable working in cloud-native, event-driven architectures.
- Excellent problem-solving and analytical skills.
Must have:
- Pyspark
- Snowflake
- Databricks
- AWS
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