What We Offer

This role provides the opportunity to drive significant impact through scalable data solutions while working with a collaborative, growth-focused team. You'll work with cutting-edge AWS technologies, solve complex data challenges, and play a key role in shaping our data platform's future. You'll learn unique graph relations models and valuable graph database experience.

Ideal for: A passionate data engineer who enjoys solving complex problems, thrives in collaborative environments, and is excited about continuous learning in the rapidly evolving data engineering landscape.

Core Technical Requirements

AWS Data Engineering Stack

• Core Services: AWS Lambda (serverless ETL functions, event-driven processing), Step Functions (workflow orchestration, state management), SQS (message queuing, decoupled architectures, dead letter queues), S3 (data lake design, partitioning strategies, lifecycle management), Glue (data catalog, ETL development, schema evolution, data lineage), CloudWatch (monitoring), RDS (warehousing)
• Relational Databases: Advanced SQL optimization, indexing strategies, query performance analysis

Data Engineering Core Skills

• Python: Advanced proficiency with AWS SDK (boto3), pandas/NumPy, data validation frameworks
• PySpark: Distributed processing, performance tuning, EMR integration, memory optimization
• SQL: Complex analytical queries, window functions, performance tuning across multiple engines
• Pipeline Architecture: End-to-end design, dependency management, fault tolerance, scalability patterns

Essential Personal & Professional Skills

End-to-End Solution Ownership

Project Leadership: Drive complex data initiatives from requirements gathering through production deployment

Stakeholder Engagement: Translate business requirements into technical solutions, manage expectations

Knowledge Sharing: Actively mentor team members, conduct technical reviews, contribute to best practices

Sprint Methodology: Thrive in iterative development cycles, participate actively in agile ceremonies

Performance Optimization: Identify bottlenecks, optimize resource utilization, reduce processing costs

Accountability & Domain Curiosity

Quality Ownership: Take personal responsibility for solution reliability, performance, and data accuracy

Business Understanding: Demonstrate genuine curiosity about different business domains and their data challenges

Proactive Improvement: Identify optimization opportunities and drive implementation without being asked

Results Focus: Commit to measurable outcomes and follow through on deliverables consistently

Experience & Background

Professional Requirements

3+ years hands-on data engineering experience with cloud-native solutions

2+ years production AWS experience building scalable data pipelines

Proven track record of end-to-end project delivery in collaborative environments

Experience with high-volume data processing (TB+ datasets, real-time streaming)

Aadvantages

Graph Databases: Relationship modeling, query optimization, integration with analytical workflows with Neptune

AI, GenAI, and Agentic Frameworks:

• Prompt engineering and LLM integration.
• AWS Bedrock for generative AI.
• MCP and orchestration frameworks (LangChain, etc.) for agent workflows

API Development: RESTful API design and implementation, Swagger/OpenAPI specification development, API documentation and testing

The goods

Fast-growing startup, big enough to still have fun and enjoy ourselves.

Our offices are located in Sapir Tower - Ramat Gan, near Savidor Merkaz train station, but we foster a remote-friendly environment, combining work from home 2 days a week.

Our perks - 10bis, bttr benefits club, happy hours, PlayStation and parking.

We believe in quality work while maintaining a work-home balance.

There is some agronomic geek stuff but it's all for the greater good :-)