Data Engineer Advisor

FedEx’s Dataworks team is hiring a Data Engineer Advisor to deliver hands-off guidance and design reviews for a GCP-based data platform and pipelines. This hybrid role in Plano, TX focuses on architecture critiques, pattern recommendations, and mentoring so teams can modernize and migrate with clarity, guardrails, and measurable outcomes.

You’ll advise on end-to-end data engineering topics across ingestion, transformation, orchestration, security, observability, metadata and lineage, and cost governance, while supporting migration and modernization under minimal supervision. The work is advisory and design-focused, with the expectation that you can translate tradeoffs into practical next steps for engineering teams.

Responsibilities

• Provide practical, hands-off guidance on GCP data platform and pipeline architecture, recommending ingestion, storage, modeling, and governance patterns aligned to organizational maturity and goals.
• Review and critique proposed GCP designs and implementation plans for scalability, reliability, security, and cost, surfacing risks and pragmatic mitigation options.
• Recommend GCP-specific ingestion and processing patterns, including Pub/Sub to Dataflow (Beam) streaming, Dataflow batch/ETL, Dataproc/Spark jobs, Transfer Service/Storage for bulk loads, and Datastream for CDC, including managed services versus containerized workload tradeoffs.
• Advise on BigQuery design and optimization, covering schema strategies, partitioning/clustering, materialized views, slots/reservations, BI Engine, cost-control approaches, and query performance best practices.
• Recommend storage and stateful service patterns on GCP, including Cloud Storage lifecycle/tiering, Bigtable/Firestore use cases, Cloud SQL/AlloyDB considerations for analytics, and caching strategies.
• Propose approaches for metadata, cataloging, and lineage using Data Catalog, Dataflow/Pub/Sub instrumentation, and integration with governance tools, defining metadata and discovery expectations.
• Advise on data quality and observability for GCP pipelines, including Dataflow validation checkpoints, Great Expectations (or similar), Cloud Monitoring/Logging instrumentation, and data SLO/SLI recommendations.
• Define security and compliance guardrails at the architecture level, including BigQuery IAM/data access models, Authorized Views, VPC Service Controls, Workload Identity, Cloud KMS/CMEK, Secret Manager, and DLP patterns for PII.
• Recommend CI/CD and deployment patterns for data workloads on GCP, including Dataflow templates, Composer/Airflow orchestration, artifact promotion strategies, and IaC (Terraform) governance.
• Provide cost and governance guidance specific to GCP analytics, including labeling, budgets, BigQuery cost controls, committed use or flat-rate considerations, and high-level FinOps guardrails.
• Create concise guidance artifacts such as GCP architecture checklists, design-review templates, migration playbooks, runbook outlines, and cutover/validation checklists.
• Mentor and upskill engineers on GCP data best practices through reviews, brown-bags, and targeted coaching.
• Support migration and modernization in an advisory capacity, contributing to risk assessments, cutover criteria, performance/RTO-RPO validation approaches, and rollback plans.

Requirements

• 5+ years in data engineering or related roles with experience advising or influencing technical direction; 2+ years working with GCP data services in a practical or architectural capacity.
• Hands-on or review experience with core GCP data services: BigQuery, Dataflow (Apache Beam), Pub/Sub, Cloud Storage, Dataproc (including Serverless), Cloud Composer (Airflow), Datastream/Transfer Service, and Data Catalog.
• Practical knowledge of BigQuery performance and cost patterns and common anti-patterns, including partitioning, clustering, materialized views, and reservations/slots.
• Familiarity with GCP security and compliance for data: IAM for datasets, Authorized Views, VPC Service Controls, Workload Identity, Cloud KMS/CMEK, Secret Manager, and DLP.
• Experience advising on pipeline observability and data quality using GCP tooling such as Cloud Monitoring/Logging, traceability for Dataflow/Dataproc jobs, and data validation frameworks.
• Experience participating in at least one GCP-focused data platform migration or modernization as an advisor, reviewer, or core contributor.
• Strong verbal and written communication skills, with the ability to produce concise, actionable guidance and explain tradeoffs to engineering and non-engineering stakeholders.
• Familiarity with Terraform and CI/CD patterns for GCP resources and data pipelines, including conceptual understanding of GitOps for data workloads.
• Certifications such as Google Professional Data Engineer or Google Cloud Architect are a plus but not required.
• Bachelor’s Degree in Information Systems, Computer Science, or a quantitative discipline such as Mathematics or Engineering, or equivalent formal training/work experience.

Benefits

• Health insurance
• Vision and dental insurance
• Retirement
• Tuition reimbursement

Location and Work Setup

• Hybrid position located in Plano, TX.
• Candidates must live within 50 miles of the campus location.
• Employees will be required to work at the FedEx campus location several times per week.
• FedEx will also consider candidates located in Pittsburgh, PA and Memphis, TN.

Compensation

Compensation range estimate for this role across potential locations: USD 10,231 - 13,812 per monthly. Actual starting pay will be determined by experience relative to the job, market level, pay at the location, and other job-related factors permitted by law. Additional pay, premiums, or bonus potential may apply.

Plano: $10,231.53/monthly - $13,812.57/monthly

Additional minimum experience context: Five to Seven (5 - 7) years equivalent work experience in measurement and analysis, quantitative business problem solving, simulation development and/or predictive analytics; extensive knowledge in data engineering and machine learning frameworks and large batch or online transaction-based systems; strong understanding of the transportation industry and evolving technologies; experience providing leadership in planning or consulting settings and as a leader or senior member of multi-function project teams; strong oral and written communication skills; and an advanced degree may offset related experience requirements.