Data Engineer III

FedEx Dataworks; Memphis (TN); Remote; USD 107,000 - 162,000; Full time

Job summary

An established industry player seeks a Data Engineer III to drive innovation in data engineering. This role involves building and optimizing data pipelines, collaborating with multi-disciplinary teams, and ensuring adherence to best practices. You'll work on cloud-based solutions, implement ETL processes, and provide mentorship to junior engineers. If you're passionate about leveraging data to create impactful solutions and thrive in a fast-paced environment, this opportunity is perfect for you. Join a team that's committed to excellence and innovation in the data space.

Benefits

Health Insurance

Vision Insurance

Dental Insurance

Retirement Plan

Tuition Reimbursement

Flexible Work Hours

Remote Work Options

Professional Development Opportunities

Qualifications

• 3-4 years experience in data engineering and predictive analytics.
• Strong understanding of data management principles and cloud technologies.
• Experience with large-scale technical solutions and data pipelines.

Responsibilities

• Design and implement ETL processes and data ingestion workflows.
• Collaborate with teams to optimize data pipelines and enhance data quality.
• Mentor junior engineers and support the Data Engineering team.

Skills

Microsoft Azure

Spark (Scala and PySpark)

SQL

NoSQL (Cassandra, MongoDB)

Kafka

ETL Processes

Data Modeling

Agile and DevOps Practices

Data Quality and Security

Python

Education

Bachelor’s Degree in Information Systems

Master’s Degree (preferred)

Tools

Azure Databricks

Azure Data Factory

Kubernetes

Docker

Terraform

Job description

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The Data Engineer III plays 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. S/he acts as a “universal translator” between IT, business, software engineers and data scientists, collaborating with these multi-disciplinary teams. The Data Engineer III 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 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. S/he will also provide mentorship and guidance to junior engineers to support the continued training and up-skilling of the Data Engineering team.

Under limited supervision, supports the design, build, test and maintenance of data pipelines at big data scale. Assists with updating data from multiple data sources. Other functionalities under limited supervision include working on batch processing of collected data and matching its format to the stored data, making 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 providing L3 support. Implements ETL transformers to reformat and enhance the data. Provides recommendations to complex problems. Provides guidance to those in less senior positions.

Job Description / Responsibilities

• 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.
  
  

Skills/Abilities

• Technical background in computer science, software engineering, database systems, distributed systems
• Extensive experience with Microsoft Azure tools to support large-scale data engineering and deployments
• 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
• 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 with the following 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
• Cloud technologies (Azure Databricks, Azure Data Factory (ADF), Azure Dev Ops (ADO)). Integrated Development Environments (IntelliJ), Java, Python, Scala.
• Working experience with Kubernetes and Docker.
• Solid understanding of data modeling, data architecture, and data management principles.
• Working knowledge of infrastructure technologies such as Terraform.
• Good to have: Pandas, Scikit-Learn, Matplotlib, TensorFlow, Jupyter and other Python data tools
  
  

DomicileInformation: 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.

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

Three to Four (3 - 4) 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.

Knolwedge, Skills And Abilities

Technical background in computer science, software engineering, database systems, distributed systemsFluency with distributed and cloud environments and a strong understanding of how to balance computational considerations with theoretical propertiesDetailed knowledge of the Microsoft Azure tooling for large-scale data engineering efforts and deployments is highly preferredA track record of designing and deploying large scale technical solutions, which deliver tangible, ongoing valueDirect experience having built and deployed robust, complex production systems that implement modern, data scientific methods at scaleAbility 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 definedDemonstrated ability to deliver technical projects with a team, often working under tight time constraints to deliver valueAn ‘engineering’ mindset, willing to make rapid, pragmatic decisions to improve performance, accelerate progress or magnify impactComfort with working with distributed teams on code-based deliverables, using version control systems and code reviewsAbility 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 deliveryDemonstrated expertise working with some of the following common languages and tools:Spark (Scala and PySpark), HDFS, Kafka and other high volume data toolsSQL and NoSQL storage tools, such as MySQL, Postgres, Cassandra, MongoDB and ElasticSearchPandas, Scikit-Learn, Matplotlib, TensorFlow, Jupyter and other Python data toolsSolid 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.

Preferred Qualifications:

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: 107,680-161,520

Additional Details: Upload a current copy of Resume (Microsoft Word or PDF format only) and answer job screening questionnaire by 5 PM CT on April 8, 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 [e-mail].

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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