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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 developing data models, data pipelines, and cloud data integration using AWS services. Proficient in SQL, Python, and data engineering best practices to ensure data quality, security, and compliance.
Highest-signal resume keywords
AWS Cloud Data IntegrationData ModelingETL/ELT Pipeline DevelopmentSQL OptimizationPython Scripting
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 ModelingETLELTSQLPythonPySparkData ArchitectureData QualityData GovernanceData Security
Soft Skills
Effective CommunicationAnalytical SkillsTroubleshootingCritical Thinking
Tools & Technologies
AWS RedshiftAWS GlueAWS LambdaAWS S3AWS AthenaAWS BedrockPower BIThoughtSpotGitHubDevOps Tools
Industry Keywords
Data LakeData WarehouseCRM IntegrationERP IntegrationData Pipeline MigrationMedallion Data ArchitectureRole-Based Access ControlData SharingLake-House PatternsAI Tools
Tech Stack
Tools & technologiesAmazon RedshiftAWSCloudERPETLOraclePandasPySparkPythonSQL
About the role
Key responsibilities & impact- Plan, design, develop, and maintain data models, data pipelines, and standards for AWS Cloud data integration, data lake, and data warehouse projects
- Ensure new features and subject areas integrate with existing structures and provide a consistent view
- Develop and maintain documentation for data architecture, data flow, and data models
- Create high-level designs and solution architectures for complex technical data engineering projects
- Participate in technical design discussions and help build and maintain medallion data architecture
- Develop and maintain AWS cloud-native data pipelines following established patterns and standards
- Design and build robust ETL/ELT pipelines from multiple sources
- Automate data ingestion, cleansing, and transformation using DevOps methodologies
- Contribute to migration of legacy pipelines to modern data architecture
- Write complex SQL, Python, and PySpark transformations and build data models supporting analytics, reporting, and downstream applications
- Monitor, optimize, and troubleshoot pipelines for reliability, scalability, security, compliance, data quality, and governance
- Collaborate with cross-functional project teams to deliver end-to-end solutions
- Communicate data solution capabilities and improvements to development and business user teams
Requirements
What you’ll need- Minimum 3 years of experience working as a Data Engineer
- Experience with cloud-based data platforms, data lakes, and cloud data warehouses such as Redshift or Snowflake
- Direct experience with traditional databases, Redshift, AWS Glue, AWS Bedrock, Athena, AWS Lambda, SageMaker, Lake Formation, IAM, SQS, S3, and other AWS core services
- Expertise in SQL and writing optimized SQL across platforms
- Expertise in Python scripting and manipulating data using Pandas/PySpark
- Familiarity with Parquet/ORC and open table formats for batch processing
- Experience integrating CRM, ERP, and marketing platforms such as Salesforce, Eloqua, and Oracle into data lakes/warehouses
- Experience in data modeling, ELT, complex stored procedures, and standard DWH and ETL/ELT concepts
- Experience with resource monitors, role-based access controls (RBAC), query performance tuning, time travel, and related advanced features
- Experience deploying data sharing, events, and lake-house patterns
- Experience with data security, data access controls, and design
- Familiarity with DevOps tools for version control, CI/CD, and GitHub
- Exposure to enterprise BI tools such as Power BI and ThoughtSpot
- Experience developing and supporting production data pipelines
- Exposure to AI and leveraging AI tools for daily tasks
- Effective communication skills and ability to translate complex technical work to business users
- Strong analytical, troubleshooting, and critical thinking skills
Benefits
Comp & perks- Flexible hybrid work model with employees in-office 2–3 days per week and remote 2–3 days per week
- Short-term incentive eligibility
- Inclusive, people-first culture
- Growth and professional development opportunities
- Equal opportunity employment