Staff Implementations Data Engineer
Build and scale distributed data ingestion, standardization, and big-data pipelines while improving platform reliability, security, and cost controls. The role requires 8+ years of data engineering experience, technical leadership, cloud deployment expertise, and strong customer-facing communication.
About the job
Responsibilities
- Develop, deploy, and continuously improve distributed, big-data pipelines powering network analysis, machine learning, data ingestion, and data fusion capabilities.
- Improve the scalability of the technology platform to meet evolving customer requirements.
- Support platform reliability, cost management, controls, customer security reviews, and accreditations.
- Serve as the technical expert in client-facing meetings, bridging government requirements and technical architecture.
- Work cross-functionally with engineers, data scientists, and product managers.
- Evaluate and recommend tools, technologies, and best practices for data pipeline development, orchestration, and deployment.
Requirements
- 8+ years of technical experience in data engineering or closely related roles.
- Extensive experience designing, developing, and maintaining complex data models from varied sources and schemas.
- Demonstrated experience leading the full lifecycle of data ingestion and standardization pipelines at scale, including design, development, testing, deployment, monitoring, and maintenance.
- Experience with sustainable software development, self-healing data workflows, data security, and data governance.
- Experience deploying and integrating software solutions across AWS, GCP, or Azure environments.
- Experience managing services such as EC2, S3, IAM, and Dockerized microservices.
- Experience leading and mentoring engineers on complex data engineering projects.
- Eligibility and willingness to obtain UK Security Check (SC) clearance, or an active clearance already.
- Excellent written and verbal communication skills, including direct interaction with external customers and stakeholders.
- Commitment to engineering excellence and knowledge sharing.
Nice to Have
- Experience managing a data platform, including monitoring releases, costs, and infrastructure changes.
- Expertise or experience deploying machine learning pipelines.
- Exposure to trade compliance, supply chain management, or international commerce.
- Experience working with or within the public sector.
- Familiarity with AI tools that improve output quality and pace.
Technologies
- Languages: Python, Spark, SQL
- Tools: AWS, Azure, Git, REST APIs, Kubernetes, Docker, Terraform, Datadog
- Datastores: Databricks, OpenSearch, Postgres
Skills
Python, Spark, SQL, AWS, Azure, GCP, Kubernetes, Docker, Terraform, Datadog, Databricks, Opensearch, Postgres, REST APIs, IAM
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