Staff Data Engineer

Walmart • Bentonville, AR

1d • $127,171 - $220,000 • Onsite

About The Position

The Staff Data Engineer translates and co-owns business problems within their discipline, identifies appropriate methods and tools, and connects business needs with tangible data-related or mathematical solutions. The role provides recommendations to business stakeholders, develops business cases, translates requirements into projects aligned with business strategy, and identifies relevant business insights.

The position identifies fit-for-purpose data sources, performs initial data-quality checks, and guides junior associates. It builds infrastructure for transforming and integrating data from diverse sources, automates repeatable data-preparation tasks, deploys pipelines with scheduling and orchestration frameworks, and evaluates data risks. The role also develops complex data models, contributes to architecture and modeling standards, and maintains data documentation and metadata.

The Staff Data Engineer reviews designs and code, develops proofs of concept, recommends testing and deployment approaches, addresses scalability, monitors production applications, and ensures code documentation is maintained. The role establishes and documents data-governance recommendations, implements governance practices with stakeholders and peers, interprets company and regulatory policies, and educates others on governance processes.

Requirements

• Bachelor's degree or equivalent in Computer Science or a related field plus 4 years of experience in software engineering or related experience; alternatively, a master's degree or equivalent in Computer Science or a related field plus 2 years of experience in software engineering or related experience.
• Experience designing and implementing scalable, optimized, distributed big-data pipelines and ETLs using frameworks such as Hadoop, Hive, Spark, and Databricks.
• Experience developing ETL pipelines with Scala, Python, Spark, and SQL.
• Experience querying and validating data using SQL and Spark SQL, and automating data validation with Spark shell scripting.
• Experience documenting data pipelines and workflows using tools such as Confluence, Jira, and Azure DevOps.
• Experience orchestrating and automating pipelines with tools such as Automic, AutoSys, Oozie, and Apache Airflow.
• Experience writing SQL to query RDBMS and data-warehousing systems such as Apache Hive and Snowflake.
• Experience developing and maintaining modules in cloud ecosystems including Google Cloud, AWS, and Azure.
• Experience working with Parquet, AVRO, CSV, ORC, and JSON, and file-based storage systems including HDFS, GCS, Azure Blob Storage, and S3.
• Experience creating and automating dashboards using Power BI, Tableau, and Looker.
• Experience leading large-scale projects and providing guidance to team members.
• Experience with system architecture, high-level design through detailed design, and disaster recovery.
• Experience with resource modeling, optimization, and forecasting.
• Experience applying incident management, change management, defect-reduction, and system-reliability processes to improve operational performance.
• Employer will accept any amount of experience with the required skills.

Responsibilities

• Translate and co-own business problems into data-related or mathematical solutions; select suitable methods and tools and explain how they address the business problem.
• Recommend solutions to complex business issues, develop project business cases, translate business requirements into aligned projects and tasks, and identify relevant business insights.
• Identify suitable data sources according to requirement priorities and service-level agreements, perform initial data-quality checks, and guide junior associates on data sources and quality.
• Build infrastructure to transform and integrate data from varied sources, automate repeatable preparation and integration tasks, and deploy pipelines using scheduling and orchestration frameworks.
• Evaluate data issues and risks early and create methods to combine and reshape complex, multi-source data for modeling.
• Assemble complex data across platforms and tools; build logical and conceptual models and guide physical data modeling.
• Define techniques for exposing data to other systems; review team modeling activities; maintain data documentation and metadata; contribute to modeling standards and architectural design.
• Review solution and application designs for business, technical, and data requirements; select development languages and libraries; map test cases to requirements and create proofs of concept.
• Review and troubleshoot code, recommend testing and deployment approaches, identify environmental modifications, and drive scalability changes.
• Monitor production applications, lead patch development when needed, and ensure code documentation is complete and periodically updated.
• Establish, modify, and document data-governance projects and recommendations; implement governance practices with stakeholders and peers.
• Interpret company and regulatory data policies, educate others on governance practices, and recommend updates to governance policies, practices, or guidelines.
• Keep current with emerging big-data analytics and data-science trends and techniques.

Benefits

• Competitive pay and performance-based incentive awards, including annual or quarterly performance incentives.
• Medical, vision, and dental coverage.
• 401(k), stock purchase, and company-paid life insurance.
• Paid time off, including sick leave, parental leave, family care leave, bereavement leave, jury duty, and voting leave.
• Short-term and long-term disability.
• Education assistance, including 100% company-paid college degrees.
• Company discounts.
• Military service pay.
• Adoption expense reimbursement.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior