Data Engineer

TSPi

. Design, modernize, and support production data pipelines that ingest, transform, validate, and publish vessel, permit, trip, declaration, landing, and enforcement-related data.

Posted 10/14/2026full-timeRemote • United StatesSeniorLead💰 $120,000 - $150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates advanced expertise in designing and supporting data pipelines using Google Cloud Platform and BigQuery, with strong SQL and programming skills in Python or Java. Proven ability to lead technical discussions, mentor teams, and ensure compliance with federal security requirements.

Highest-signal resume keywords

Data Pipeline DesignGoogle Cloud PlatformAdvanced SQL SkillsTechnical LeadershipREST API Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ProcessingSQLPythonJavaBigQueryCloud RunCloud FunctionsDataflowInfrastructure as Code

Soft Skills

Technical LeadershipMentoringCommunicationCross-Functional CollaborationProblem-Solving

Tools & Technologies

GitGitHubDockerCloud StoragePub SubComposerAutomated TestingContinuous IntegrationDeployment PipelinesCloud Observability Tools

Industry Keywords

Federal Security RequirementsData GovernanceVessel MonitoringMaritime DataRegulatory Compliance

Tech Stack

Tools & technologies

BigQueryCloudDockerGoogle Cloud PlatformJavaPythonSQL

About the role

Key responsibilities & impact

Design, modernize, and support 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.
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.
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 cloud storage, orchestration, service identities, secrets, configuration, networking, and environment-specific deployment settings.
Improve continuous integration and delivery pipelines and establish 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 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 stakeholder communication.
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.
Provide technical leadership for data pipelines, interfaces, and cloud services supporting federal government vessel and enforcement information systems.

Requirements

What you’ll need

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.
Successful candidates must be able to pass a government background investigation and satisfy public trust requirements.
US Citizenship or US Green Card is required.
Preferred: Deep experience with BigQuery, Cloud Run, Cloud Functions, Pub Sub, Cloud Storage, Dataflow, Composer, or related Google Cloud services.
Preferred: Experience developing enterprise data architecture, reusable integration frameworks, data governance practices, or platform modernization roadmaps.
Preferred: Experience with fisheries, vessel monitoring, maritime, geospatial, regulatory, or enforcement data.
Preferred: Experience with Docker, infrastructure as code, automated data-quality testing, orchestration, and cloud observability tools.
Preferred: Experience defining operational metrics, service-level objectives, health dashboards, and alerts for business-critical data pipelines.
Preferred: Experience supporting federal information systems and leading technical work within federal security, accessibility, change-control, and release-management requirements.