<p>I’m building a world-class team to power our next generation of data products. We’re looking for a Senior Data Engineer who knows AWS inside and out—someone who can <strong>design secure, scalable data pipelines</strong>, <strong>own ETL/ELT workflows</strong>, <strong>engineer cloud data infrastructure</strong>, and <strong>deliver dimensional and semantic models</strong> that our analysts, data scientists, and applications can trust.</p><p>You’ll work closely with product, security, platform engineering, and analytics to move our architecture toward a <strong>real-time, governed, cost-aware</strong>, and <strong>highly automated</strong> data ecosystem.</p><p><strong>What You’ll Do</strong></p><ul><li><strong>Design & build end-to-end pipelines</strong> on AWS (batch and streaming) using services like <strong>Glue, EMR, Lambda, Step Functions, Kinesis, MSK</strong>, and <strong>Fargate</strong>.</li><li><strong>Develop robust ETL/ELT</strong> (PySpark, Spark SQL, SQL, Python) for structured, semi-structured, and unstructured data at scale.</li><li><strong>Own data storage & processing layers</strong>: <strong>S3 (Lake/Lakehouse), Redshift (or Snowflake on AWS), DynamoDB</strong>, and <strong>Athena</strong> with strong partitioning, compaction, and performance tuning.</li><li><strong>Implement data models</strong> (3NF, dimensional/star, Data Vault, Lakehouse medallion) for analytics and operational workloads.</li><li><strong>Engineer secure infrastructure-as-code</strong> with <strong>Terraform</strong> (or <strong>CDK</strong>) across multi-account setups; implement CI/CD via <strong>GitHub Actions</strong> or <strong>AWS CodeBuild/CodePipeline</strong>.</li><li><strong>Harden security & governance</strong>: use <strong>IAM</strong>, <strong>Lake Formation</strong>, <strong>KMS</strong>, <strong>Secrets Manager</strong>, <strong>VPC/PrivateLink</strong>, <strong>GLUE Catalog</strong>, and fine-grained access controls. Partner with SecOps on compliance (e.g., <strong>SOC 2</strong>, <strong>FedRAMP</strong>, <strong>HIPAA</strong> depending on dataset).</li><li><strong>Observability & reliability</strong>: build monitoring with <strong>CloudWatch</strong>, <strong>OpenTelemetry</strong>, and data quality checks (e.g., <strong>Great Expectations</strong>, <strong>Deequ</strong>), implement SLOs and alerts.</li><li><strong>Champion best practices</strong>: code reviews, testing (unit/integration), documentation, runbooks, and blameless postmortems.</li><li><strong>Mentor</strong> mid-level engineers and collaborate on architectural decisions, standards, and technical roadmaps.</li></ul><p><br></p>
<p>Since it’s 2026, the Data Engineering landscape in DC has shifted heavily toward <strong>Cloud-Native architectures</strong> and <strong>GenAI-ready pipelines</strong>. Robert Half typically recruits for both their internal corporate teams and their high-end consulting arm (Protiviti).</p><p>Here is a tailored job description based on current 2026 market standards and Robert Half’s specific hiring trends in the District.</p><p><br></p><p>Job Title: Data Engineer</p><p><strong>Location:</strong> Washington, DC (Hybrid – Downtown DC Office)</p><p><strong>Company:</strong> Robert Half </p><p><strong>Employment Type: </strong>Contract-to-Hire</p><p>Role Overview</p><p>As a Data Engineer at Robert Half, you will be the backbone of our data-driven decision-making process. You aren't just "moving data"; you are architecting the flow of information that powers our localized market analytics and global recruitment engines. In the DC market, this often involves handling high-compliance data environments and integrating cutting-edge AI frameworks into traditional ETL workflows.</p><p><br></p><p><br></p>
We are looking for a skilled Data Engineer to join our team in Washington, District of Columbia. In this role, you will play a key part in designing and implementing secure, scalable solutions to support data and analytics initiatives. This is a long-term contract position, offering the opportunity to work with cutting-edge technologies and contribute to impactful projects.<br><br>Responsibilities:<br>• Develop, test, and maintain robust data pipelines and engineering solutions to support analytics and integrate new data sources.<br>• Collaborate with team members, stakeholders, and external vendors to evaluate and implement reliable, scalable, and secure technologies.<br>• Create efficient, automated processes to handle repetitive data management tasks.<br>• Conduct targeted data manipulation and analysis across diverse datasets.<br>• Implement advanced security measures within data warehouses and analytics platforms to counter evolving threats.<br>• Document technical processes and solutions to ensure seamless collaboration and knowledge sharing.<br>• Monitor and optimize system performance to ensure scalability and reliability.<br>• Stay updated on emerging data engineering trends and incorporate them into workflows.