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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 scalable data pipelines, managing cloud-based data platforms, and ensuring data quality and security. Proficient in data migration and modernization initiatives, with a strong focus on business intelligence and analytics support.
Highest-signal resume keywords
SQLPythonAWS (S3, Glue, Redshift, Lambda, Athena)Data WarehousingETL/ELT Pipeline Development
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
PySparkData LakesDimensional Data ModelingData MigrationSpark/DatabricksPipeline OrchestrationData QualityInfrastructure as CodeStreaming TechnologiesData Governance
Tools & Technologies
Power BITableauQuickSightAirflowAzure Data FactorySnowflakeMicrosoft FabricTerraformCloudFormationBicep
Certifications & Qualifications
AWS Data EngineerDP-203DP-600
Industry Keywords
Data IntegrationData TransformationOperational StabilityBusiness IntelligenceAnalytics
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSAzureCloudETLKafkaPySparkPythonSparkSQLTableauTerraform
About the role
Key responsibilities & impact- Design, develop, and maintain scalable data pipelines and integration frameworks
- Manage and optimize cloud-based data platforms, databases, data warehouses, and analytical datasets
- Lead and support data migration, modernization, and transformation initiatives
- Collaborate with business, analytics, and reporting teams to deliver reliable and trusted data assets
- Ensure data quality, security, performance, availability, and operational stability
- Support BI, reporting, and self-service analytics initiatives
- Monitor, troubleshoot, and continuously improve data platform operations and processes
Requirements
What you’ll need- Strong hands-on experience in SQL, Python, and/or PySpark
- Experience designing and developing ETL/ELT pipelines, data flows, and integration solutions
- Hands-on experience with AWS (S3, Glue, Redshift, Lambda, Athena) and/or Azure (ADF, Databricks, ADLS, Synapse)
- Strong knowledge of Data Warehousing, Data Lakes, Lakehouse architectures, and dimensional data modeling (Star/Snowflake)
- Experience building and supporting enterprise data platforms for reporting, analytics, and business intelligence
- Hands-on experience in data migration and modernization projects, including on-premises to cloud migrations and legacy platform transformations
- Experience with Spark/Databricks and large-scale data processing
- Knowledge of batch and real-time data processing frameworks
- Experience with pipeline orchestration tools such as Airflow, ADF, Step Functions, or equivalent
- Strong understanding of data quality, validation, performance tuning, and operational support
- Experience supporting BI solutions using Power BI, Tableau, QuickSight, or similar platforms
- Familiarity with source control, CI/CD, and Agile delivery methodologies
- Experience with Snowflake, Microsoft Fabric, or similar modern data platforms
- Exposure to streaming technologies such as Kafka, Event Hub, or Kinesis
- Knowledge of CDC, replication, and data synchronization frameworks
- Experience with Infrastructure as Code using Terraform, CloudFormation, or Bicep
- Understanding of Data Governance, Metadata Management, Data Lineage, and Security practices
- Cloud certifications such as AWS Data Engineer, DP-203, DP-600, or equivalent