Senior Data Engineer

Senior Data EngineerLocation: Baltimore - 4 days per week on-site & 1 WFHSalary: $170-190k + Bonus + BenefitsType: PermanentNo Sponsorship AvailableAbout the Company:Our client is a global AI and data technology business focused on transforming critical industries through advanced data platforms, AI, and intelligent infrastructure solutions. They partner with governments, utilities, telecoms, healthcare providers, and enterprise organisations to deliver scalable, real-world impact across highly complex environments.The organisation operates across the full technology lifecycle, from architecture and engineering through to deployment and operational capability building, leveraging cloud-native technologies and modern data platforms.The Opportunity:We’re looking for a Senior Data Engineer to design, build, and optimise scalable data platforms supporting advanced analytics, machine learning, AI, and operational intelligence solutions. This role will focus on building modern cloud-native data architectures capable of handling large-scale, multi-source data workloads across batch, streaming, and near real-time environments. You’ll work closely with Data Scientists, ML Engineers, Product teams, and senior stakeholders to deliver robust, production-grade data capabilities.The environment is highly engineering-led, with a strong focus on:Data as a ProductScalability & reliabilityObservability & governanceModern lakehouse architecturesDistributed processing frameworksAI & advanced analytics enablementKey Responsibilities:Design and develop scalable cloud-native data platforms and architecturesBuild robust ingestion and transformation pipelines across APIs, IoT/telemetry, legacy systems, and structured data sourcesDevelop distributed data processing capabilities using technologies such as Spark and KafkaImplement modern lakehouse/data platform architectures supporting analytics, GIS, AI, and machine learning workloadsEstablish best practices around observability, monitoring, data quality, lineage, and platform reliabilityDesign secure, governed data environments with strong access controls, encryption, and auditabilityCollaborate with Data Scientists and ML Engineers to operationalise AI and advanced analytics solutionsOptimise platform performance, scalability, and cost efficiencyContribute to architectural strategy and mentor junior engineers within the teamSupport CI/CD, infrastructure automation, and cloud deployment best practicesRequired Experience:5+ years’ experience building and operating large-scale data platforms in cloud or hybrid environmentsStrong experience designing modern data architectures including lakehouse, data mesh, or equivalent frameworksHands-on expertise with distributed processing technologies such as Spark/PySparkExperience with streaming/event-driven architectures using Kafka or similar technologiesStrong Python and SQL development skillsExperience working with modern data tooling such as dbt, Docker, and cloud-native platformsExposure to AWS, Azure, or GCP environmentsStrong understanding of data governance, security, access controls, encryption, and auditabilityExperience integrating complex and heterogeneous data sourcesAbility to design highly available, production-grade data systemsExperience enabling machine learning and AI workloads through scalable data infrastructureDesirable Experience:Experience within regulated, public sector, utilities, infrastructure, or government environmentsKnowledge of Infrastructure-as-Code and CI/CD practicesExposure to AI/ML operationalisation and feature engineering pipelinesExperience working within highly distributed, multi-stakeholder organisationsTechnology Stack:PythonSQLPySpark / SparkKafkaDatabricksdbtDockerAWS / Azure / GCPPersonal Attributes:Strong systems-thinking and problem-solving mindsetComfortable operating within fast-paced, complex environmentsCollaborative and highly communicativePassionate about scalable engineering and platform reliabilityProactive, delivery-focused, and accountableStrong stakeholder engagement skills across technical and non-technical teams