Data Engineer

Seeking 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 pipelines
• Build and enhance CI/CD pipelines supporting reliable data engineering deployments
• Develop ingestion and transformation pipelines across legacy systems, APIs, IoT/telemetry, relational databases, and other data sources
• Design cloud-native architectures supporting batch, streaming, and near-real-time workloads
• Build distributed and event-driven data processing solutions using Spark, Kafka, or equivalent technologies
• Develop modern lakehouse and data warehouse architectures using technologies such as Databricks and dbt
• Write clean, maintainable, production-quality code using Python and SQL
• Implement automated testing, monitoring, observability, data-quality validation, lineage, and reliability standards
• Build secure and governed data environments incorporating RBAC, encryption, auditability, and access controls
• Support data infrastructure that enables analytics and future machine learning and AI use cases
• Optimize data platforms for performance, scalability, reliability, and cost
• Partner with engineers, data scientists, technical teams, and client stakeholders to translate requirements into scalable solutions
• Troubleshoot complex production issues and take ownership of solutions through resolution
• Contribute to architectural decisions and the long-term evolution of the data platform

• 5 years of professional data engineering experience, including designing and operating production data platforms
• Strong hands-on Python and SQL experience
• Strong experience with Spark/PySpark and distributed data processing
• Experience with Kafka, event streaming, or comparable streaming technologies
• Experience designing and building modern data architectures such as lakehouses, data warehouses, data lakes, or distributed data platforms
• Experience with Databricks, dbt, or comparable modern data technologies
• Experience integrating multiple data sources including APIs, legacy systems, relational databases, and/or telemetry/IoT data
• Experience with AWS, Azure, and/or GCP
• Experience building or supporting CI/CD pipelines and production deployment processes
• Understanding of Infrastructure as Code and cloud-native engineering practices
• Experience building highly available, observable, production-grade data systems
• Understanding of data governance, security, access controls, encryption, lineage, and auditability
• Strong troubleshooting, systems-thinking, and problem-solving skills
• Ability to independently own technical deliverables from design through production
• Strong communication and stakeholder collaboration skills
• Comfortable working directly with clients in complex, high-visibility environments
• Ability to accommodate approximately 50-75% onsite work in Baltimore through a regular travel/onsite rotation, * Experience supporting government, public-sector, federal-adjacent, defense, infrastructure, healthcare, financial services, or another regulated environment
• Experience with Databricks, dbt, Docker, Spark/PySpark, and Kafka
• Experience designing secure data platforms subject to regulatory or compliance requirements
• Familiarity with HIPAA, CJIS, FERPA, state privacy requirements, or similar security and privacy frameworks
• Experience with Infrastructure as Code and automated cloud deployments
• Experience supporting analytics, GIS, machine learning, or AI applications through robust data infrastructure
• Experience with IoT, telemetry, infrastructure, or other complex real-world datasets
• Experience working within globally distributed engineering teams
• Previous consulting or client-facing engineering experience