Staff, Data Engineer
About The Position
The Staff Data Engineer translates and co-owns business problems within the discipline, identifying suitable data-related or mathematical solutions, methods, and tools. The role provides recommendations to business stakeholders on complex issues, develops project business cases, translates business requirements into aligned project activities, and connects business needs with practical solutions and insights. The position identifies appropriate data sources, performs initial data-quality checks, and guides junior associates. It builds infrastructure and automated pipelines to transform and integrate data from varied sources, using scheduling and orchestration frameworks. The engineer assesses data risks, reshapes complex multi-source data for modeling, and stays current with big data analytics and data science techniques. Responsibilities also include assembling complex data across platforms; building logical and conceptual models; guiding physical modeling; defining techniques for exposing data to other systems; maintaining data documentation and metadata; and contributing to modeling standards and architectural design. The role reviews application designs, develops and tests code, creates proofs of concept, troubleshoots production applications, drives scalability improvements, and maintains code documentation. It establishes and implements data governance practices, interprets company and regulatory policies, educates others, and applies defined data strategy to business problems. The position is located at 811 Excellence Dr, Bentonville, AR 72716.
Requirements
- Master's degree or equivalent in Computer Science, Information Technology, Engineering, or a related field and 2 years of experience in software engineering or related experience; OR a bachelor's degree or equivalent in one of those fields and 4 years of such experience.
- Experience designing, developing, and testing relational database management systems, including MySQL, Microsoft SQL Server, or Postgres.
- Experience working in a fast-paced environment using Agile methodologies.
- Experience with data warehousing concepts, methodologies, and frameworks using distributed technologies such as SparkSQL, Hadoop, Kafka, and Hive.
- Experience designing and developing analytical dashboards using Business Intelligence reporting tools such as Tableau, PowerBI, or Looker.
- Experience coding in object-oriented programming languages such as Java, Python, or Scala.
- Experience coding in scripting languages such as Python, Shell scripts, Ruby, or Perl.
- Experience with software engineering best practices across the development lifecycle, including Agile methodologies, coding standards, code reviews, source control management, build processes, testing, and operations, using tools such as Git and Jenkins.
- Experience identifying business use cases and transforming business problems into scalable analytical solutions.
- Experience using IDE tools such as VSCode or IntelliJ.
- Experience identifying and debugging issues related to the business domain and designing solutions.
- Experience with data structures and algorithms.
- The employer will accept any amount of graduate coursework, graduate research experience, or experience with the required skills.
Responsibilities
- Translate or co-own business problems and identify suitable data-related or mathematical solutions, methods, and tools.
- Provide recommendations to business stakeholders, develop project business cases, translate business requirements into activities and tasks, and align work with business strategy.
- Identify appropriate data sources, understand requirements and service-level agreements, perform initial data-quality checks, and guide junior associates on data sourcing and quality.
- Build infrastructure and automated processes to transform and integrate data from multiple sources, and deploy pipelines using scheduling and orchestration frameworks.
- Evaluate data issues and risks, and develop methods to fuse and reshape complex multi-source data for modeling.
- Assemble complex data across platforms and tools; build logical and conceptual models; guide physical data modeling; and define methods for exposing data to other systems.
- Maintain data documentation and metadata, contribute to data modeling standards and best practices, and provide architectural design input.
- Review solution and application designs, select development languages and libraries, map test cases to requirements, create proofs of concept, and troubleshoot code.
- Recommend testing methods, deployment environments, and application changes needed for different environments and scalability.
- Monitor production applications and lead development of patches when required; ensure code documentation is complete and current.
- Establish, document, and implement data governance projects and practices in partnership with stakeholders and peers.
- Interpret company and regulatory data policies, educate others on governance processes, and recommend policy or guideline updates.
- Understand and apply defined data strategy principles to business problems.
- Keep current with big data analytics and data science trends and techniques.
Benefits
- Medical, vision, and dental coverage
- 401(k)
- Stock purchase
- Company-paid life insurance
- Paid time off, including sick leave
- Parental leave
- Family care leave
- Bereavement leave
- Jury duty leave
- Voting leave
- Short-term and long-term disability
- Education assistance, including 100% company-paid college degrees
- Company discounts
- Military service pay
- Adoption expense reimbursement
- Performance-based incentive awards, including annual or quarterly performance incentives
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What This Job Offers
Job Type
Full-time
Career Level
Senior
