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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining scalable data pipelines using PySpark and Airflow, while ensuring data quality and compliance with governance standards. Proficient in data modeling techniques and architectures, particularly in data lakehouse and warehousing solutions.
Highest-signal resume keywords
Data EngineeringPySparkAirflowGoogle Cloud PlatformData Modeling Techniques
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringData Pipeline DevelopmentData IntegrationData TransformationData Quality AssuranceData GovernanceData WarehousingData Lakehouse ArchitectureGraphQLBusiness Intelligence
Soft Skills
CollaborationProblem-SolvingCommunication
Tools & Technologies
Google Cloud PlatformDataprocAirflowPySpark
Industry Keywords
Data GovernanceRegulatory ComplianceData SecurityData ArchitectureBusiness Analytics
Tech Stack
Tools & technologiesAirflowCloudGoogle Cloud PlatformGraphQLPySpark
About the role
Key responsibilities & impact- Translate complex business requirements into scalable data engineering solutions aligned with organizational strategy
- Design, develop, and maintain data pipelines and workflows using PySpark, Airflow, and Google Cloud Platform
- Implement data modeling techniques for data warehousing and lakehouse architectures, ensuring data quality and security
- Collaborate with stakeholders to identify data sources and perform data integration, transformation, and validation
- Apply data governance policies and ensure compliance with regulatory and ethical standards
- Monitor and troubleshoot data processes to optimize performance and reliability
- Provide guidance on data architecture best practices and documentation
- Support Walmart’s APEX Data and Architecture team in building and maintaining an AI-ready Data Lakehouse
Requirements
What you’ll need- Bachelor’s degree in Computer Science and 4 years' experience in software engineering or related field; or 6 years' experience in software engineering or related field; or Master's degree in Computer Science and 2 years' experience in software engineering or related field
- 3 years' experience in data engineering, database engineering, business intelligence, or business analytics
- Proficiency with PySpark, Airflow, and Google Cloud Platform services such as Dataproc
- Strong knowledge of data modeling techniques, data lakehouse architectures, and data warehousing solutions
- Experience ensuring data quality, security, and governance in compliance with regulatory and ethical standards
- Ability to design, develop, and maintain scalable data pipelines integrating internal and external data sources
- Experience designing and implementing federated graphs in GraphQL
- Demonstrated capability to translate complex business requirements into effective data solutions
- Applicants must be authorized to work for any employer in the United States without current or future visa sponsorship
Benefits
Comp & perks- Incentive awards for performance
- 401(k) match
- Stock purchase plan
- Paid maternity and parental leave
- PTO
- Multiple health plans