Data Engineer
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Role details
Tech stack
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Job description
- Design, develop, and maintain scalable ETL/ELT pipelines to ingest, transform, and load data from multiple sources
- Build and optimize data workflows supporting both batch and real-time processing
- Ensure high availability and reliability of data pipelines across enterprise systems
AWS Cloud & Data Services
- Leverage AWS services such as S3, Glue, Lambda, Redshift, EMR, and Kinesis to support data engineering solutions
- Design and manage cloud-based data architectures that are secure, scalable, and cost-efficient
- Implement best practices for data storage, partitioning, and lifecycle management
Data Optimization & Performance
- Optimize data storage and retrieval for performance, scalability, and cost efficiency
- Implement indexing, partitioning, and query optimization strategies
- Monitor and troubleshoot data pipeline performance issues
Data Quality & Governance
- Ensure data accuracy, consistency, and integrity across all data pipelines and systems
- Implement validation, monitoring, and error-handling mechanisms
- Support data governance practices and compliance with security and IC standards
Collaboration & Integration
- Work closely with data scientists, software engineers, and mission stakeholders to support analytics and operational needs
- Integrate data solutions with enterprise applications, APIs, and downstream analytics platforms
- Participate in Agile development processes and contribute to continuous improvement efforts
Requirements
The ideal candidate will have strong experience with AWS cloud services, data engineering best practices, and big data technologies, with the ability to operate in a fast-paced, collaborative environment supporting complex mission systems., Active TS/ SCI W/ Polygraph Required.
Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent experience)
Demonstrated experience in data engineering and pipeline development
Strong experience with AWS data services (e.g., S3, Glue, Redshift, Lambda, EMR)
Proficiency in SQL and Python for data processing and transformation
Experience working with large-scale data sets and big data technologies
Strong analytical and problem-solving skills
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