Overview
On Site
$120,000 - $130,000
Full Time
Skills
Agile
Amazon Kinesis
Amazon Lambda
Amazon Redshift
Amazon S3
Amazon Web Services
Apache Kafka
Apache Spark
Business Intelligence
Cloud Computing
Collaboration
Continuous Delivery
Continuous Integration
Data Analysis
Data Engineering
Data Lake
Data Modeling
Data Quality
Data Security
Data Warehouse
Electronic Health Record (EHR)
Encryption
ELT
Extract
Transform
Load
Git
Management
Microsoft Power BI
Orchestration
Privacy
PySpark
Python
Real-time
Regulatory Compliance
SQL
Snow Flake Schema
Star Schema
Step-Functions
Storage
Streaming
Tableau
Terraform
Version Control
Warehouse
Workflow
Job Details
Job Summary:
We are seeking an experienced AWS Data Engineer to design, build, and maintain scalable data pipelines and infrastructure on the AWS cloud platform. The ideal candidate will have a strong understanding of cloud-native data solutions, ETL development, and data modeling, with hands-on experience using core AWS services such as S3, Glue, Redshift, Lambda, and EMR.
Key Responsibilities:
Design and develop data ingestion, transformation, and storage pipelines using AWS services.
Build and optimize ETL/ELT workflows using AWS Glue, AWS Lambda, or Apache Spark on EMR.
Implement and manage data lake and warehouse solutions (e.g., Amazon S3, Redshift, Athena, Lake Formation).
Work closely with data analysts, data scientists, and business stakeholders to deliver reliable data solutions.
Ensure data quality, lineage, and governance practices are maintained across all datasets.
Monitor and optimize data pipeline performance and cost efficiency.
Develop and maintain infrastructure-as-code (IaC) using CloudFormation or Terraform.
Support data security, privacy, and compliance best practices.
Collaborate in agile teams to deliver scalable, maintainable, and high-quality solutions.
Required Skills and Qualifications:
Bachelor s degree in Computer Science, Information Systems, or a related field.
3 7 years of experience in data engineering or related roles.
Strong expertise in AWS data services such as S3, Glue, Redshift, Athena, EMR, and Lambda.
Experience with SQL and data modeling (Star Schema, Snowflake Schema, etc.).
Hands-on experience with Python or PySpark for ETL development.
Knowledge of data lake and data warehouse architectures.
Familiarity with CI/CD pipelines and version control (Git).
Understanding of data security and governance (IAM, KMS, encryption).
Preferred Qualifications:
AWS Certified Data Analytics Specialty or AWS Certified Solutions Architect.
Experience with real-time data streaming (Kinesis, Kafka).
Exposure to orchestration tools (Airflow, Step Functions).
Experience with BI tools (QuickSight, Power BI, Tableau).
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.