Data Engineer - CLEARED

The Squires Group•Washington, DC

1d•$65 - $75•Remote

About The Position

Our client is a large global integrator. They are seeking a Data Engineer to design, develop, and optimize secure, scalable enterprise data solutions supporting the modernization and cloud migration of their background investigation system, leveraging AWS data platforms, modern data architectures, and advanced ETL/ELT technologies. Per our Federal Government Contract, candidates must be U.S. Citizens with an ACTIVE TOP SECRET CLEARANCE.

Requirements

Active Top Secret (TS) clearance required on Day 1, with the ability to complete adjudication or transfer requirements as applicable.
Security+ certification required on Day 1.
7+ years of experience designing, building, and supporting enterprise data engineering solutions and modern data platforms.
Strong expertise with relational databases, including PostgreSQL, Oracle, and SQL Server, as well as semi-structured and NoSQL data sources such as DynamoDB, JSON, and APIs.
Extensive experience with Medallion Architecture (Bronze, Silver, Gold) and dimensional data modeling for analytics and operational reporting.
Hands-on experience with Amazon Redshift.
Hands-on experience developing scalable ETL/ELT pipelines using AWS Glue, Apache Spark/PySpark, SQL, and Python.
Experience implementing CDC using AWS DMS and integrating operational databases with analytical platforms.
Strong knowledge of AWS data services, including S3, Glue, Redshift, Lambda, EventBridge, SQS/SNS, IAM, CloudWatch, and Secrets Manager.
Experience developing metadata-driven ingestion frameworks, data lineage, and data quality validation processes.
Proficiency in data modeling, schema evolution, data versioning, and master/reference data management.
Strong understanding of event-driven architectures and application/database synchronization patterns.
Experience optimizing SQL queries, Spark jobs, partitioning strategies, indexing, and Redshift performance for large-scale datasets.
Experience working in Agile/Scrum environments and collaborating with application developers, architects, and business stakeholders.
Excellent verbal and written communication skills.

Nice To Haves

AWS Certified Data Engineer – Associate or AWS Certified Solutions Architect certification.
Experience designing enterprise data lakes and lakehouse architectures.
Experience implementing enterprise metadata repositories and data catalogs.
Familiarity with Qlik and AWS Glue Data Catalog.
Experience supporting real-time and near-real-time data integration architectures.

Responsibilities

Design scalable, secure, and high-performance database architectures supporting application modernization and cloud migration initiatives.
Define data models, schemas, and storage strategies aligned with cloud and analytics requirements.
Design and implement enterprise data lakes, lakehouse architectures, and Medallion Architecture (Bronze, Silver, Gold).
Develop and maintain scalable ETL/ELT pipelines using AWS Glue, Apache Spark/PySpark, SQL, and Python.
Implement Change Data Capture (CDC) using AWS DMS to synchronize operational databases with analytical platforms such as Amazon Redshift.
Leverage data lakes to capture and organize functionality-specific data to support business and application requirements.
Collaborate with application, infrastructure, and the clients teams to identify data requirements, support user stories, and maintain a unified data model.
Optimize database, SQL, Spark, and Redshift performance for large-scale datasets, including indexing and partitioning strategies.
Design and support data ingestion frameworks, data lineage, data quality validation, schema evolution, and data versioning processes.
Ensure data architectures and solutions comply with applicable data governance, security, privacy, and retention requirements.
Support event-driven architectures and application/database synchronization patterns using AWS services.
Document database architectures, configurations, data models, and operational procedures.
Collaborate with developers, architects, business stakeholders, and Agile/Scrum teams to deliver enterprise data solutions.