Data Engineer 4

TSPi is seeking a Data Engineer 4 to support the federal government. This position will provide technical leadership for the data pipelines, interfaces, and cloud services that collect, transform, validate, and deliver vessel and enforcement-related information to operational applications and reporting tools.

The successful candidate will serve as a senior member of an established Agile delivery team and work with federal product owners, architects, application developers, data engineers, testers, and regional stakeholders. The role requires deep hands-on experience with Google Cloud Platform, BigQuery, SQL, APIs, pipeline architecture, and production operations. The engineer will own technically complex integrations, guide design decisions, mentor team members, and improve the reliability, observability, security, maintainability, and cost efficiency of the broader data ecosystem.

• Contribute to the design, modernization, and support of production data pipelines that ingest, transform, validate, and publish vessel, permit, trip, declaration, landing, and enforcement-related data.
• Define scalable integration patterns for batch, scheduled, event-driven, streaming, and API-based workloads based on operational and mission requirements.
• Translate business and technical needs into source-to-target mappings, canonical models, schema strategies, transformation logic, reference-data rules, and data-quality controls.
• Design and optimize complex SQL and data-processing logic for ingestion, reconciliation, analytics, reporting, and application support.
• Establish approaches for data lineage, versioning, backward compatibility, and controlled schema evolution across interconnected systems.
• Lead technical reviews, set engineering standards, and guide source-code, configuration, testing, and release practices through Git or GitHub workflows.

• Architect and implement secure, resilient data workloads using BigQuery and other Google Cloud Platform services.
• Guide the design of cloud storage, orchestration, service identities, secrets, configuration, networking, and environment-specific deployment settings.
• Improve continuous integration and delivery pipelines and establish consistent, automated deployments across development, test, staging, and production environments.
• Evaluate architectural tradeoffs and improve performance, scalability, cost efficiency, recoverability, and operational visibility.
• Apply federal security requirements, least-privilege access, encryption, auditability, and secure service-to-service communication practices.

• Define monitoring and service-level indicators for pipeline health, processing volume, latency, failures, data quality, and downstream impact.
• Lead the diagnosis and resolution of complex issues involving source data, database connections, APIs, credentials, transformation logic, schedules, dependencies, and cloud services.
• Establish standards for alerting, structured logging, retry handling, failure recovery, reprocessing, reconciliation, and operational readiness.
• Coordinate releases, production validation, incident response, root-cause analysis, corrective actions, and communication with technical and program stakeholders.
• Own and review architecture diagrams, interface documentation, data dictionaries, decision records, runbooks, deployment procedures, and known-issue records.
• Mentor engineers, facilitate technical design discussions, estimate complex work, identify delivery risks, and contribute to backlog refinement, sprint planning, demonstrations, and retrospectives.

• Minimum 9 years of professional experience in data engineering, systems integration, software engineering, or a related role, including responsibility for complex production systems.
• Advanced experience designing, building, and supporting data pipelines in Google Cloud Platform or a comparable cloud environment.
• Advanced SQL skills and demonstrated experience designing solutions with BigQuery, relational databases, or cloud data warehouses.
• Strong proficiency with Python, Java, or another language used for production data-processing and integration services.
• Demonstrated experience designing REST API integrations, data contracts, schema-evolution strategies, mappings, transformations, and reconciliation processes.
• Experience leading production troubleshooting, incident response, root-cause analysis, and resolution of complex data-quality or integration issues.
• Experience establishing Git or GitHub workflows, code-review standards, automated testing, continuous integration, and deployment pipelines.
• Ability to assess an existing architecture and codebase, identify technical risk, and assume ownership of mission-critical services with limited oversight.
• Strong technical leadership, documentation, communication, mentoring, and cross-functional collaboration skills in an Agile environment.
• Bachelor's degree in computer science, information systems, data engineering, or a related field, or equivalent practical experience.

• Deep experience with BigQuery, Cloud Run, Cloud Functions, Pub Sub, Cloud Storage, Dataflow, Composer, or related Google Cloud services.
• Experience developing enterprise data architecture, reusable integration frameworks, data governance practices, or platform modernization roadmaps.
• Experience with fisheries, vessel monitoring, maritime, geospatial, regulatory, or enforcement data, including permit, trip, logbook, declaration, landing, or reference-data sources.
• Experience with Docker, infrastructure as code, automated data-quality testing, orchestration, and cloud observability tools.
• Experience defining operational metrics, service-level objectives, health dashboards, and alerts for business-critical data pipelines.
• Experience supporting federal information systems and leading technical work within federal security, accessibility, change-control, and release-management requirements.

Successful candidates must be able to pass a government background investigation and satisfy public trust requirements. US Citizenship or US Green Card is required.

Originally posted on Himalayas