This is a full-time, on-site role for a Data Engineer at WideOps Ltd., located in Haifa. The Data Engineer will design, build, and maintain scalable data pipelines, implement robust Extract, Transform, Load (ETL) processes, and develop efficient data models to support business intelligence and data analytics needs. The role also involves building and improving data warehousing solutions and collaborating with cross-functional teams to ensure data integrity and optimize workflows.
Qualifications
Core Data Engineering
3+ years of experience as a Data Engineer
Strong hands-on experience with Google Cloud Platform
Advanced SQL (BigQuery performance, partitioning, clustering)
Strong Python (data pipelines, APIs, batch & streaming jobs)
Experience building batch and streaming pipelines
BigQuery
Dataflow / Apache Beam
Pub/Sub
Cloud Storage
Data modeling for analytics and ML use cases
Production troubleshooting, optimization, and cost awareness
ML & GenAI
Experience supporting ML pipelines (training, inference, feature prep)
Hands-on with at least one of:
Vertex AI
Feature stores
Model inference pipelines
Experience working with LLM-based systems, including:
Embeddings generation
Vector databases / similarity search
RAG-style pipelines
Ability to prepare, version, and serve data for GenAI / ML workloads
Platform & Engineering
Experience with Airflow / Cloud Composer or equivalent orchestration
CI/CD pipelines for data & ML workloads
Infrastructure-as-code familiarity (Terraform preferred)
Understanding of IAM, data security, and access controls on GCP
Nice to Have
Experience with FinOps / cost optimization
Experience with real-time ML or low-latency inference
Experience with monitoring & observability for data/ML pipelines
Google Cloud certifications (Data Engineer / Architect)
Core Data Engineering
3+ years of experience as a Data Engineer
Strong hands-on experience with Google Cloud Platform
Advanced SQL (BigQuery performance, partitioning, clustering)
Strong Python (data pipelines, APIs, batch & streaming jobs)
Experience building batch and streaming pipelines
BigQuery
Dataflow / Apache Beam
Pub/Sub
Cloud Storage
Data modeling for analytics and ML use cases
Production troubleshooting, optimization, and cost awareness
ML & GenAI
Experience supporting ML pipelines (training, inference, feature prep)
Hands-on with at least one of:
Vertex AI
Feature stores
Model inference pipelines
Experience working with LLM-based systems, including:
Embeddings generation
Vector databases / similarity search
RAG-style pipelines
Ability to prepare, version, and serve data for GenAI / ML workloads
Platform & Engineering
Experience with Airflow / Cloud Composer or equivalent orchestration
CI/CD pipelines for data & ML workloads
Infrastructure-as-code familiarity (Terraform preferred)
Understanding of IAM, data security, and access controls on GCP
Nice to Have
Experience with FinOps / cost optimization
Experience with real-time ML or low-latency inference
Experience with monitoring & observability for data/ML pipelines
Google Cloud certifications (Data Engineer / Architect)
