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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 building scalable cloud-native data platforms on AWS, with strong capabilities in ETL/ELT pipeline development, data modeling, and AI solution architecture. Proficient in both Hebrew and English, with a focus on translating business requirements into technical designs and ensuring platform reliability.
Highest-signal resume keywords
AWS Data ServicesETL/ELT Pipeline DevelopmentData Warehouse DesignAdvanced SQLPython 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
Data EngineeringData ArchitectureCloud-Native ArchitecturesReal-Time Data PipelinesData ModelingOrchestrationGovernanceObservabilityCI/CDInfrastructure as Code
Soft Skills
Interpersonal SkillsProactive AttitudeOwnership
Tools & Technologies
DatabricksDBTSnowflakeAirflowKafkaSparkRedshiftS3AWS GlueLambda
Industry Keywords
FintechGamingRetailProfessional ServicesManaged Services
Tech Stack
Tools & technologiesAirflowAmazon RedshiftAWSCloudETLKafkaKubernetesMicroservicesPythonSparkSQL
About the role
Key responsibilities & impact- Design and build scalable cloud-native data platforms and modern lakehouse architectures on AWS under the guidance of senior leadership
- Build and maintain robust ETL/ELT pipelines, streaming architectures, and data services
- Apply best practices for data modeling, orchestration, governance, and observability to ensure platform scalability
- Assist in architecting modern AI solutions, including RAG pipelines, vector search, and ML integrations
- Work closely with customers and internal teams to translate business requirements into functional technical designs
- Participate in troubleshooting, code reviews, performance tuning, and production support to drive platform reliability
- Support modernization projects involving the transition from legacy ETL systems to cloud-based data warehouses
Requirements
What you’ll need- Fluency in Hebrew and English is mandatory
- 4–6 years of hands-on experience in Data Engineering, Data Architecture, or Backend Engineering
- Solid experience implementing cloud-native architectures and leveraging AWS data services
- Strong hands-on experience with at least 4-5 of the following: Databricks, DBT, Snowflake, Airflow, Kafka, Spark, Redshift, S3, AWS Glue, or Lambda
- Advanced SQL and Python development skills
- Experience with data warehouse design, lakehouse architectures, and building scalable real-time data pipelines
- Understanding of CI/CD, Infrastructure as Code (IaC), and monitoring practices
- Excellent interpersonal skills with a "people person" attitude and the ability to engage in technical discussions with customers
- A proactive, can-do attitude with a strong sense of ownership over assigned projects
- Experience with Amazon Bedrock, SageMaker, or vector databases
- Exposure to Kubernetes or microservices architectures
- Experience in high-scale environments such as fintech, gaming, or retail
- Previous experience in a Professional Services or Managed Services environment
- Familiarity with data quality and observability frameworks
Benefits
Comp & perks- Competitive salaries
- Bonus incentives
- Benefits
- Flexible hours
- Mentoring
- Learning and personal development opportunities