We're looking for a Senior Data Infrastructure Engineer to help us build the data foundation that powers everything does. You'll be joining the Data Platform team in TLV, working on the infrastructure that ingests, processes, and governs data across a growing stack of products, customers, and microservices - structured and unstructured, streaming and batch. The work you do here sits at the core of how every team makes decisions.
We believe three things matter for every role : drive to push through challenges, efficiency that keeps standards high while moving fast, and adaptability that lets you pivot with data and AI insights. These aren't buzzwords, they're how we actually work.
Our AI-first approach isn't just a tagline either. We're building the future of insurance with AI at the center, and we need people who are genuinely excited to learn and grow alongside these tools.
In this role youll:
Design and implement data solutions for all application requirements in a distributed microservices environment
Build ingestion layers and a data lake using streaming ETLs and Change Data Capture
Implement large-scale batch and streaming pipelines with modern data processing frameworks
Build pipelines and scheduling infrastructures that other teams rely on every day
Ensure data quality, compliance, and governance across entire data platform
Help shape data-mesh concepts that empower other teams to leverage data independently
Partner with Data Engineers, ML Engineers, Data Scientists, BI Engineers, and Product Managers to move fast and build right
Requirements: At least 5 years of experience as a Data Engineer or Data Infrastructure Engineer
A bachelor's degree in Computer Science or a related field
Deep knowledge of databases - SQL and NoSQL
Proven experience building large-scale data infrastructures, including Change Data Capture, streaming pipelines, and customer data platforms
Hands-on experience with Python, Pulumi/Terraform, Apache Spark, Snowflake, AWS, Kubernetes, and Kafka
Familiarity with open source tools like Airflow and DBT
Familiarity with AI concepts like RAG, embeddings, and LLM context engineering - a plus
Enthusiasm about learning and adapting to the exciting world of AI - a commitment to exploring this field is a fundamental part of our culture
Ready to work in an office environment most days of the week
This position is open to all candidates.