Data Engineer with Security Clearance

OVERVIEW: We are seeking a talented and motivated Data Engineer to join our growing team. In this role, you will be instrumental in building and maintaining robust data pipelines and infrastructure on AWS. You will have the opportunity to work with cutting-edge technologies, solve complex data challenges, and contribute directly to data-driven decision-making within the organization. GENERAL DUTIES: Design, develop, and maintain scalable and reliable ETL (Extract, Transform, Load) pipelines from various data sources to target destinations using AWS services.
Utilize AWS services such as AWS Glue, Amazon Kinesis, and Amazon EMR to build and manage efficient data ingestion and processing workflows.
Transform raw data into usable formats, applying programming concepts and best practices to ensure data quality and consistency.
Design and implement effective data models and select appropriate data storage solutions based on business requirements, including Amazon S3, Amazon Redshift, and/or Amazon DynamoDB.
Establish and maintain a comprehensive data catalog, documenting data schemas and managing data lifecycles.
Implement and monitor data quality checks and processes to ensure accuracy and consistency across all data stores.
Collaborate with data scientists, analysts, and other stakeholders to understand their data needs and provide effective data solutions.
Contribute to the continuous improvement of our data infrastructure and processes.
Apply general knowledge of networking, storage, and compute concepts in the context of cloud-based data solutions.
REQUIRED QUALIFICATIONS: A minimum of 4 years of professional experience in data engineering or data architecture.
At least 2 years of hands-on experience working with Amazon Web Services (AWS).
Proven experience in setting up and maintaining ETL pipelines using AWS services like AWS Glue, Amazon Kinesis, and Amazon EMR.
Demonstrated ability to transform data using ETL processes and apply programming concepts (e.g., Python, Scala, SQL).
Experience designing data models and selecting appropriate data storage solutions such as Amazon S3, Amazon Redshift, and/or Amazon DynamoDB.
Familiarity with data cataloging and data lifecycle management principles.
A strong understanding of data quality principles and experience implementing data quality checks.
General knowledge of networking, storage, and compute concepts.
AWS Certified Data Engineer certification CLEARANCE: Top Secret clearance minimum