AWS Data Engineer

AWS Data Engineer

Location: Remote

Role Type: 6-month contract 
 

About Our Client
Our client is a well-established organization that delivers innovative technology and engineering solutions to both public and private sectors. They operate nationwide and have a proven track record of supporting large-scale transformation initiatives. Their mission centers around advancing technology, optimizing performance, and delivering high-value solutions to their customers.

Job Description
Leidos is seeking an AWS Data Engineer to design, build, and optimize large-scale data pipelines and analytics solutions on Amazon Web Services (AWS). The role will design and build the infrastructure and pipelines that enable organizations to collect, store, process, and analyze large volumes of structured and unstructured data efficiently and securely. A Data Engineer is responsible for the end-to-end data lifecycle, from ingestion and transformation to storage and delivery for analytics, machine learning, and operational systems. They ensure data is reliable, high-quality, scalable, and accessible for business and technical stakeholders.
The ideal candidate will have strong expertise in cloud-based data engineering, hands-on experience with AWS native services, and a solid understanding of data lake, data warehouse, and real-time streaming architectures.

Duties and Responsibilities
• Design, build, and optimize ETL/ELT workflows to ingest data from multiple sources. (e.g., S3, Redshift, Lake Formation, Glue, lambda).
• Implement data cleansing, enrichment, and standardization processes.
• Automate batch and streaming data pipelines for real-time analytics. Build solutions for both streaming (Kinesis, MSK, Lambda) and batch processing (Glue, EMR, Step Functions).
• Ensure pipelines are optimized for scalability, performance, and fault tolerance.
• Optimize SQL queries, data models, and pipeline performance.
• Ensure efficient use of cloud-native resources (compute, storage, networking).
• Design and implement data architecture across data lakes, data warehouses, and lakehouses.
• Optimize data storage strategies (partitioning, indexing, schema design).
• Implement data integration from diverse sources (databases, APIs, IoT, third-party systems).
• Work with Data Scientists, Analysts, and BI developers to deliver clean, well-structured data.
• Document data assets and processes for discoverability.
• Training of existing core staff who will maintain infrastructure and pipelines.

Required Experience/Skills
• Bachelor’s degree in Computer Science, Data Engineering, or related field.
• 5+ years of experience in data engineering roles
• Proficiency in SQL, Python, or Scala for data transformation and processing.
• Experience in the utility industry data
• Strong understanding of utility data domains: meter data, customer data, grid/asset data, work management, outage data.
• Familiarity with CIM standards and utility integration frameworks.
• Working Knowledge of AWS services such as:
• Storage & Processing: S3, Glue, Redshift, Athena, EMR
• Streaming: Kinesis, MSK, Lambda

Education
Bachelor’s degree in Computer Science, Data Engineering, or related field

Pay & Benefits Summary

• Pay rate up to 57/h W2

Keyword | AWS Data Engineer | Data Pipeline | Data Lake | Redshift | Glue | EMR | Kinesis | Python | Scala | SQL