Data Analyst Advisor

The Data Engineer Advisor plays a pivotal role within Fed Ex, focused on creating and driving engineering innovation within Dataworks, helping define and build the organization and facilitate 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 Advisor will contribute to the creation of and adherence to 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 Fed Ex and into data products and services that may be externally facing. Day-to-day, s/he will be deeply involved in code reviews and large-scale deployments. Under minimal supervision, supports the design, build, test and maintain data pipelines at big data scale.

Assists with updating data from multiple data sources. Other functionalities under close supervision is to work on batch processing of collected data and match its format to the stored data, make sure that the data is ready to be processed and analyzed. Assists with keeping the ecosystem and the pipeline optimized and efficient, troubleshooting standard performance, data related problems and provide L3 support.

Independently implements parsers, validators, transformers and correlators to reformat, update and enhance the data. Provides recommendations to highly complex problems. Provides guidance to those in less senior positions.

Essential Functions

• Advanced Data Pipeline Engineering:
  Design, build, and deploy highly scalable, fault-tolerant batch and real-time streaming data pipelines utilizing core Google Cloud Platform services such as Dataflow, Dataproc, Confluent Kafka and Pub/Sub.
• Big Query & Data Warehouse Optimization:
  Develop complex ELT/ETL workflows and implement efficient physical data models in Big Query, focusing on query optimization, partitioning, and clustering for high-performance analytics.
• Technical Mentorship & Advisory:
  Serve as a technical authority on the team, guiding junior engineers, conducting rigorous code reviews, and establishing standard methodologies for robust data platform development.
• Platform Automation & Orchestration:
  Implement Infrastructure as Code (IaC) and robust CI/CD pipelines to automate deployments, seamlessly orchestrating complex data workflows using Cloud Composer (Airflow) and Terraform.
• Cross-Functional Solution Delivery:
  Partner closely with Data Architects, IT stakeholders, and business teams to translate complex architectural designs and use cases into actionable, production-ready engineering tasks.
• System Reliability & Cost Tuning:
  Proactively monitor data platform health, troubleshoot performance bottlenecks, resolve data ingestion failures, and optimize Google Cloud Platform resource utilization to ensure maximum efficiency and cost-effectiveness.

Knowledge, Skills, and Abilities

• Google Cloud Platform Pipeline Engineering Mastery:
  Expert-level proficiency in building scalable, fault-tolerant batch and streaming pipelines using Big Query, Dataflow, Dataproc, Confluent Kafka and Pub/Sub.
• Advanced Programming & Orchestration:
  Deep technical expertise in Python, SQL, and Cloud Composer (Airflow) for complex data transformation, ELT/ETL, and workflow automation.
• Cloud Dev Ops & Infrastructure as Code:
  Strong hands-on experience with Terraform, CI/CD pipelines, and platform performance tuning to deploy and manage high-availability cloud infrastructure.

Minimum Education

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

Minimum Experience

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 including design, development and implementation of highly complex…