Data Engineer, Hebrew Speaker

This is a fully remote position, open to applicants in Romania.

📋 Description

• Design and develop scalable, cloud-native data platforms and modern lakehouse architectures on AWS, guided by senior leadership.

• Construct and uphold robust ETL/ELT pipelines, streaming architectures, and data services.

• Implement best practices for data modeling, orchestration, governance, and observability to guarantee platform scalability.

• Assist in developing modern AI solutions, including RAG pipelines, vector search capabilities, and machine learning integrations.

• Collaborate closely with customers and internal teams to translate business needs into effective technical designs.

• Engage in troubleshooting, code reviews, performance optimization, and production support to enhance platform reliability.

• Aid in modernization projects that involve transitioning from legacy ETL systems to cloud-based data warehouses.

⛳️ Requirements

• Proficiency in both Hebrew and English is required.

• 4–6 years of practical experience in Data Engineering, Data Architecture, or Backend Engineering.

• Strong experience in implementing cloud-native architectures and utilizing AWS data services.

• Significant hands-on experience with at least 4-5 of the following: Databricks, DBT, Snowflake, Airflow, Kafka, Spark, Redshift, S3, AWS Glue, or Lambda.

• Advanced skills in SQL and Python development.

• Experience with data warehouse design, lakehouse architectures, and the creation of scalable real-time data pipelines.

• Familiarity with CI/CD, Infrastructure as Code (IaC), and monitoring methodologies.

• Excellent interpersonal skills with a personable approach and the ability to partake in technical discussions with clients.

• A proactive, can-do attitude with a strong sense of accountability for 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.

• Prior experience in a Professional Services or Managed Services setting.

• Knowledge of data quality and observability frameworks.

🏝️ Benefits

• Competitive salaries.

• Bonus incentives.

• Comprehensive benefits.

• Flexible working hours.

• Mentorship opportunities.

• Opportunities for learning and personal development.