Data Engineer

Data EngineerSeeking an experienced Data Engineer to join a global technology organization as it expands its U.S. presence and supports a high-impact, federal-adjacent initiative in Baltimore.This is a hands-on engineering role focused on designing, building, and maintaining secure, scalable data platforms and CI/CD pipelines within a complex client environment. The Data Engineer will work with large and varied datasets across legacy systems, APIs, telemetry/IoT sources, and modern cloud platforms while helping establish reliable infrastructure for analytics and future AI/ML capabilities.The ideal candidate has strong production data engineering experience, thrives in client-facing environments, and can independently solve complex technical problems while collaborating with distributed teams and stakeholders.Day-to-Day Responsibilities:Design, build, and maintain scalable, production-grade data platforms and pipelinesBuild and enhance CI/CD pipelines supporting reliable data engineering deploymentsDevelop ingestion and transformation pipelines across legacy systems, APIs, IoT/telemetry, relational databases, and other data sourcesDesign cloud-native architectures supporting batch, streaming, and near-real-time workloadsBuild distributed and event-driven data processing solutions using Spark, Kafka, or equivalent technologiesDevelop modern lakehouse and data warehouse architectures using technologies such as Databricks and dbtWrite clean, maintainable, production-quality code using Python and SQLImplement automated testing, monitoring, observability, data-quality validation, lineage, and reliability standardsBuild secure and governed data environments incorporating RBAC, encryption, auditability, and access controlsSupport data infrastructure that enables analytics and future machine learning and AI use casesOptimize data platforms for performance, scalability, reliability, and costPartner with engineers, data scientists, technical teams, and client stakeholders to translate requirements into scalable solutionsTroubleshoot complex production issues and take ownership of solutions through resolutionContribute to architectural decisions and the long-term evolution of the data platformMinimum Requirements:5+ years of professional data engineering experience, including designing and operating production data platformsStrong hands-on Python and SQL experienceStrong experience with Spark/PySpark and distributed data processingExperience with Kafka, event streaming, or comparable streaming technologiesExperience designing and building modern data architectures such as lakehouses, data warehouses, data lakes, or distributed data platformsExperience with Databricks, dbt, or comparable modern data technologiesExperience integrating multiple data sources including APIs, legacy systems, relational databases, and/or telemetry/IoT dataExperience with AWS, Azure, and/or GCPExperience building or supporting CI/CD pipelines and production deployment processesUnderstanding of Infrastructure as Code and cloud-native engineering practicesExperience building highly available, observable, production-grade data systemsUnderstanding of data governance, security, access controls, encryption, lineage, and auditabilityStrong troubleshooting, systems-thinking, and problem-solving skillsAbility to independently own technical deliverables from design through productionStrong communication and stakeholder collaboration skillsComfortable working directly with clients in complex, high-visibility environmentsAbility to accommodate approximately 50–75% onsite work in Baltimore through a regular travel/onsite rotationPreferred Qualifications:Experience supporting government, public-sector, federal-adjacent, defense, infrastructure, healthcare, financial services, or another regulated environmentExperience with Databricks, dbt, Docker, Spark/PySpark, and KafkaExperience designing secure data platforms subject to regulatory or compliance requirementsFamiliarity with HIPAA, CJIS, FERPA, state privacy requirements, or similar security and privacy frameworksExperience with Infrastructure as Code and automated cloud deploymentsExperience supporting analytics, GIS, machine learning, or AI applications through robust data infrastructureExperience with IoT, telemetry, infrastructure, or other complex real-world datasetsExperience working within globally distributed engineering teamsPrevious consulting or client-facing engineering experience