Data Engineer II & III (All Levels) ID - 10813
- Company: FedEx Dataworks
- Category: Professional
- Employment Type: Full Time
- Worker Sub-Type: Regular Remote Worker
- Remote: Yes
-
Location:
- 3680 Hacks Cross Road, Memphis, TN 38125-8800, United States
- Remote
Description
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.
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Duties for this role include but not limited to: supporting the design, build, test and maintain data pipelines at big data scale. Assists with updating data from multiple data sources. 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. Assisting with keeping the ecosystem and the pipeline optimized and efficient, troubleshooting standard performance, data related problems and provide L3 support. Implementing parsers, validators, transformers and correlators to reformat, update and enhance the data. Provides recommendations to highly complex problems. Providing guidance to those in less senior positions.
Essential Functions
About the Role - Our Data Engineers play a pivotal role within Dataworks, focused on driving engineering innovation within Dataworks, helping define and build the Dataworks organization and leading the delivery of key business initiatives. He or she acts as a “universal translator” between IT, business, software engineers and data scientists, collaborating with these multi-disciplinary teams. This person will contribute to the adherence of technical standards for data engineering, including the selection and refinements of foundational technical components. Swill 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, he or she will be deeply involved in code reviews and large-scale deployments. He or she will also provide mentorship and guidance to junior engineers to support the continued training and up-skilling of the Data Engineering team.
- 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 techniques
- Delivering tangible value very rapidly, collaborating with complementary teams of varying backgrounds and subject areas
- Championing the adherence to 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
- Design, implement and optimize ETL processes, data ingestion, and integration workflows on cloud environments
- Implement best practices for data management, including data quality and security.
- Implement cloud-based data storage solutions, leveraging technologies for performance and cost efficiency
- Identify opportunities for automation and process improvement within the data engineering workflow
- Stay updated with emerging technologies and trends in data engineering to enhance our systems and processes
Knowledge, Skills, Abilities
- Technical background in computer science, software engineering, database systems, distributed systems
- Fluency with distributed and cloud environments and a strong 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 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 quickly while adopting new and evolving technologies and apply to projects
- 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 tools
- Solid understanding of data modeling, data architecture, and data management principles.
- Proven track record of solving complex problems and delivering high-quality, scalable solutions
- Technical background in computer science, software engineering, database systems, distributed systems
- Fluency with distributed and cloud environments and a strong 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 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 quickly while adopting new and evolving technologies and apply to projects.
- 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 tools
- Solid understanding of data modeling, data architecture, and data management principles
- Proven track record of solving complex problems and delivering high-quality, scalable solutions
- Excellent communication and collaboration skills to work effectively in a team environment
- Proficiency in data modeling, data visualization, Infrastructure as Code, and Kubernetes
Minimum Qualifications and Education
Data Engineer II:
Bachelor's Degree in Computer Science, Information Systems, a related quantitative field such as Engineering or Mathematics or equivalent formal training or work 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.
Data Engineer III:
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 (5) 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 batch or online transaction-based systems. Strong understanding of the transportation industry, competitors, and evolving technologies. Experience providing leadership in a general planning or consulting setting. Experience as a senior member of multi-functional project teams. Strong oral and written communication skills. A related advanced degree may offset the related experience requirements.
Domicile Information
This position can be domiciled anywhere in the United States. The ability to work remotely within the United States may be available based on business needs.
Pay Transparency:This compensation range is provided as a reasonable estimate of the current starting salary range for this role across all potential locations. If this opportunity includes multiple job levels, the range is a reasonable estimate of the current starting salary for the lowest level to the current starting salary of the highest level. Actual starting pay would be determined by experience relative to the job, market level, pay at the location for this job and other job-related factors permitted by law. An employee may be eligible for additional pay, premiums, or bonus potential. The Company offers eligible employees health, vision and dental insurance, retirement, and tuition reimbursement.
Pay:Pay Range: 82,320 – $161,520
Additional Details:Application Criteria: Upload current copy of Resume (Microsoft Word or PDF format only) and answer job screening questionnaire by 5 pm Central April 13, 2025.
FedEx Dataworks is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
Dataworks does not discriminate against qualified individuals with disabilities in regard to job application procedures, hiring, and other terms and conditions of employment. Further, Dataworks is prepared to make reasonable accommodations for the known physical or mental limitations of an otherwise qualified applicant or employee to enable the applicant or employee to be considered for the desired position, to perform the essential functions of the position in question, or to enjoy equal benefits and privileges of employment as are enjoyed by other similarly situated employees without disabilities, unless the accommodation will impose an undue hardship. If a reasonable accommodation is needed, please contact
