About FedEx Dataworks:
Born out of FedEx, a pioneer that ships nearly 20 million packages a day and manages endless threads of information, FedEx Dataworks is an organization rooted in connecting the physical and digital sides of our network to meet today's needs and address tomorrow's challenges.
We are creating opportunities for FedEx, our customers, and the world at large by:
• Exploring and harnessing data to define and solve true problems
• Removing barriers between data sets to create new avenues of insight
• Building and iterating on solutions that generate value
• Acting as a change agent to advance curiosity and performance
• At FedEx Dataworks, we are making supply chains work smarter for everyone.
Summary:
The Data Engineer Lead plays a pivotal role within Dataworks, focused on creating and driving engineering innovation within Dataworks, helping define and build the Dataworks 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 Lead 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 Dataworks 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 reviews and large-scale deployments.
Job Description / Responsibilities :
• Understanding in depth both business and technical problems Dataworks aims to solve.
• Building tools, platforms and pipelines to enable teams to clearly and cleanly analyze data, build models and drive decisions.
• Scaling up from "laptop-scale" to "cluster scale" problems, in terms of both infrastructure and problem structure and technique.
• Delivering tangible value very rapidly, collaborating with diverse teams of varying backgrounds and disciplines
• Codifying best practices for future reuse in the form of accessible, reusable patterns, templates, and code bases
• Interacting with senior technologists from the broader enterprise and outside of FedEx (partner ecosystems and customers) to create synergies and ensure smooth deployments to downstream operational systems
Skills/Requirements
• Technical background in computer science, software engineering, database systems, distributed systems.
• Fluency with distributed and cloud environments and a deep understanding of how to balance computational considerations with theoretical properties
• Detailed knowledge of the Microsoft Azure tooling for large-scale data engineering efforts and deployments is highly preferred
• A compelling track record of designing and deploying large scale technical solutions, which deliver tangible, ongoing value
• Direct experience having built and deployed robust, complex production systems that implement modern, data scientific methods at scale
• Ability to context-switch, to provide support to dispersed teams which may need an "expert hacker" to unblock an especially challenging technical obstacle, and to work through problems as they are still being defined.
• Demonstrated ability to deliver technical projects with a team, often working under tight time constraints to deliver value.
• An 'engineering' mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impact
• Comfort with working with distributed teams on code-based deliverables, using version control systems and code reviews.
• Ability to conduct data analysis, investigation, and lineage studies to document and enhance data quality and access
• Use of agile and devops practices for project and software management including continuous integration and continuous delivery.
• Demonstrated expertise working with some of the following common languages and tools:
• Spark (Scala and PySpark), HDFS, Kafka and other high-volume data tools
• SQL and NoSQL storage tools, such as MySQL, Postgres, Cassandra, MongoDB and ElasticSearch
• Pandas, Scikit-Learn, Matplotlib, TensorFlow, Jupyter and other Python data tool
• flink, kubernetes, and databricks.
Minimum Qualifications:
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. 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 systems and data pipelines. Extensive knowledge in Information Systems including design, development and implementation of large
Location: Memphis, TN
Posted: Nov. 8, 2024, 9:24 p.m.
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