Data Engineer

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Ind Contributor Remote, US

5 days ago Requisition

Salary Range: $ To $ Annually

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, Big Query, 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 Git Hub workflows.
• Architect and implement secure, resilient data workloads using Big Query 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 Big Query, relational databases, or cloud data warehouses.
• Strong proficiency with Python, Java, or another language used for production data-processing and integration services.
• Demonstrated experience…