Data Engineer II

Domicile Information: This is a hybrid position located in Memphis TN, Plano TX, or Pittsburgh PA. 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.

Business Summary

The Data Engineer II plays an important role within , focused on delivering engineering innovation within , helping to execute the delivery of key business initiatives. S/he acts as a “universal translator” between IT, business, software engineers and data scientists, collaborating with these multi-disciplinary teams. The Data Engineer II will contribute to the adherence of technical standards for data engineering, including the selection and refinements of foundational technical components. S/he will work on those aspects of the platform that govern the ingestion, transformation, and pipelining of data assets, both to end users within FedEx and into data products and services that may be externally facing. Day-to-day, s/he will be deeply involved in code development and medium-scale deployments.

Essential Functions

Build and operate data pipelines on GCP: implement batch and streaming workflows using Dataflow (Beam), Dataproc/Spark, Pub/Sub, Transfer Service, and Cloud Storage.

Develop and maintain BigQuery datasets and ETL/ELT jobs: design schemas, implement partitioning/clustering, write performant SQL, and create materialized views where appropriate.

Implement data ingestion patterns and CDC integrations (Datastream, Pub/Sub connectors, or Kafka bridging) and handle schema evolution and backfills.

Author reliable, testable pipeline code and artifacts (Python/Java/Scala), implement unit/integration tests, and enforce schema/versioning practices.

Instrument pipelines and jobs for observability: add logging, metrics, traces; configure Cloud Monitoring/Logging alerts and data-SLIs for freshness/completeness.

Implement data quality checks and validation (Great Expectations, custom checks) and escalate data incidents; participate in runbook creation and incident response.

Apply security and compliance controls in day-to-day work: follow dataset IAM patterns, use Workload Identity/Service Accounts, integrate Secret Manager and Cloud KMS/CMEK where needed, and apply DLP patterns for PII.

Collaborate in design reviews and follow architecture/playbooks defined by senior architects/advisors; propose practical improvements and flag risks.

Contribute to CI/CD and deployment for data workloads: templated Dataflow deployments, Airflow/Composer DAG management, Terraform basics for provisioning data resources.

Optimize cost and performance at the implementation level: query tuning, storage format choices (Parquet/Avro), lifecycle policies for Cloud Storage, and recommend reservation/slot sizing for BigQuery.

Produce clear documentation and runbooks for owned pipelines, mentor junior engineers and hand off operational ownership where applicable.

Preferred Qualifications

2-3 years of professional data engineering experience (or equivalent), with hands-on ownership of data pipelines and analytics workloads.

1–2 years working with GCP data services: BigQuery, Dataflow (Beam), Pub/Sub, Cloud Storage, Dataproc, and Cloud Composer (Airflow).

Strong SQL skills and practical programming experience in Python, Java, or Scala; production experience with Spark or Beam preferred.

Familiarity with streaming patterns, CDC, and at least one message/streaming system (Pub/Sub, Kafka).

Experience with data quality/testing frameworks (Great Expectations, Deequ) and observability tooling (Cloud Monitoring/Logging, tracing for Dataflow/Dataproc).

Working knowledge of GCP security features relevant to data (dataset IAM, VPC Service Controls awareness, Secret Manager, Cloud KMS basics).

Experience with version control (Git), CI/CD pipelines, and basic infrastructure-as-code (Terraform) for provisioning and reproducible deployments.

Good problem-solving and collaboration skills; able to communicate technical issues and tradeoffs to peers and stakeholders.

Google Professional Data Engineer certification or similar cloud/data cert is a plus but not required.

Minimum Education

Bachelor's Degree in Computer Science, Information Systems, a related quantitative field such as Engineering or Mathematics or equivalent formal training or work experience.

Minimum Experience

Two (2) years equivalent work experience in measurement and analysis, quantitative business problem solving, simulation development and/or predictive analytics. Strong knowledge in data engineering and machine learning frameworks including design, development and implementation of highly complex systems and data pipelines. Strong knowledge in Information Systems including design, development and implementation of large batch or online transaction-based systems. Strong understanding of the transportation industry, competitors, and evolving technologies. Experience as a member of multi-functional project teams. Strong oral and written communication skills. A related advanced degree may offset the related experience requirements.

Preferred Qualifications:

Pay Transparency:

Pay:  US: $7,094.23/mo - $15,607.31/mo, CO: $7,094.23/mo - $14,957.01/mo, MD: $7,488.36/mo - $15,607.31/mo, NJ: $7,488.36/mo - $15,607.31/mo, NY: $7,488.36/mo - $15,607.31/mo, NYC: $9,064.85/mo - $15,607.31/mo, WA: $7,488.36/mo - $15,607.31/mo

Additional Details:

For details on our comprehensive benefits, click here .

Federal Express Corporation is an Equal Opportunity Employer including, Vets/Disability.

Reasonable accommodations are available for qualified individuals with disabilities throughout the application process. Applicants who require reasonable accommodations in the application or hiring process should contact recruitmentsupport@fedex.com .

Applicants have rights under Federal Employment Laws:

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Family and Medical Leave Act (FMLA)

Employee Polygraph Protection Act

E-Verify Program Participant: Federal Express Corporation participates in the Department of Homeland Security U.S. Citizenship and Immigration Services’ E-Verify program (For U.S. applicants and employees only). Please click below to learn more about the E-Verify program:

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