We are looking for an experienced Data Engineer for a permanent opportunity in Northern, Virginia. In this role, you will design reliable data solutions that support analytics and business decision-making while helping improve the overall data environment. The ideal candidate brings strong technical depth in modern data engineering practices and enjoys building scalable systems from the ground up. <br> Responsibilities: • Design, develop, and maintain robust data pipelines that collect, transform, and deliver high-quality data for reporting and analysis. • Create and optimize data models that support business intelligence, analytics, and operational use cases across the organization. • Build and manage ETL workflows using Python and related technologies to ensure efficient movement of data between systems. • Work with large-scale data processing tools such as Apache Spark and Hadoop to handle complex and high-volume datasets. • Integrate streaming and batch data sources using technologies such as Apache Kafka to support timely and reliable data availability. • Collaborate with analysts, engineers, and business stakeholders to translate data needs into scalable engineering solutions. • Improve data warehouse performance, structure, and reliability to support accurate and accessible enterprise data. • Use dbt and other modern data transformation practices to organize, test, and document datasets effectively.
<p>We are looking for a Data Automation Engineer to design, develop, and maintain scalable data automation solutions leveraging AWS cloud services, selected Azure technologies, and emerging Generative AI capabilities.</p><p><br></p><p><strong>Key Responsibilities:</strong></p><p>· Design and implement scalable data automation workflows using AWS services with integration to Azure platforms.</p><p>· Develop and maintain ETL/ELT processes to ingest, transform, and move data across DynamoDB, SQL Server, Azure SQL, and other enterprise data sources.</p><p>· Build and support batch and near real-time data pipelines using Apache Spark and streaming technologies such as Kafka or Flume.</p><p>· Develop scalable data processing solutions utilizing Amazon EMR, AWS Fargate, Kubernetes, and related cloud technologies.</p><p>· Integrate REST APIs, external services, and Amazon Connect customer interaction data into analytics platforms.</p><p>· Evaluate and prototype Generative AI solutions using Amazon Bedrock, Azure OpenAI, Hugging Face, LangChain, and related technologies.</p><p>· Implement source control, CI/CD, and automation practices using GitHub, Azure DevOps, Jenkins, Docker, and Agile methodologies.</p><p>· Ensure data solutions meet security and compliance requirements, including IAM, encryption, RBAC, VPC isolation, and firewall policies.</p>