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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 implementing scalable data architectures, particularly using Databricks, Apache Spark, and cloud platforms like AWS, Azure, or GCP. Proven ability to translate customer requirements into effective data solutions while providing technical guidance and support.
Highest-signal resume keywords
DatabricksApache Spark / PySparkData EngineeringSolution ArchitectureSQL
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 EngineeringSQLPythonLakehouse ArchitectureData Pipeline DesignBig Data ArchitectureData IngestionData TransformationData ProcessingCloud Platform Integration
Soft Skills
Excellent CommunicationCustomer-Facing ExperienceConsulting ExperiencePresentation Skills
Tools & Technologies
DatabricksApache SparkPySparkDelta LakeUnity CatalogAWSAzureGCP
Industry Keywords
Data ArchitectureData ModernizationTechnical WorkshopsArchitecture DemonstrationsTechnical Documentation
Tech Stack
Tools & technologiesApacheAWSAzureCloudGoogle Cloud PlatformPySparkPythonSparkSQLUnity
About the role
Key responsibilities & impact- Work directly with enterprise customers as a trusted technical advisor
- Understand customer business and technical requirements and translate them into scalable data architectures
- Design and implement modern Lakehouse / Data + AI architectures using Databricks
- Develop and guide POCs, technical workshops, and architecture demonstrations
- Work extensively with Apache Spark / PySpark, SQL, and Databricks
- Design scalable data ingestion, transformation, and processing pipelines
- Work with Delta Lake, Unity Catalog, and Databricks platform capabilities
- Support data migration and modernization initiatives
- Integrate Databricks with AWS, Azure, or GCP
- Troubleshoot performance, scalability, reliability, and data pipeline issues
- Collaborate with customer engineering, data science, architecture, and leadership teams
- Provide technical recommendations around data engineering, analytics, ML/AI, and cloud architecture
- Create reference architectures, technical documentation, and implementation guidance
- Support production deployment and adoption of Databricks solutions
- Conduct technical workshops, enablement sessions, and knowledge-sharing activities
Requirements
What you’ll need- 9+ years of experience
- Strong experience with Databricks
- Strong Apache Spark / PySpark skills
- Strong SQL skills
- Strong data engineering fundamentals
- Experience designing data pipelines / data platforms
- Experience with Lakehouse / Data Warehouse / Big Data architecture
- Experience with at least one cloud platform: AWS, Azure, or GCP
- Strong customer-facing / consulting experience
- Architecture/design experience
- Excellent communication and presentation skills
- Must-have skills: Data Engineering, Python, Solution Architecture
- Good-to-have skills: SQL, Azure, Databricks