Senior Big Data & AI Engineer / Technical Lead

We are looking for a hands-on, high-profile Senior Big Data & AI Engineer / Technical Lead to join our core engineering team in Israel. In this role, you will take technical ownership over mission-critical data initiatives, driving complex data architectures from concept to production.

In this role, you will design and execute advanced data workflows, build scalable architectures across modern data warehouses, implement AI agents, and expand our machine learning capabilities. We need someone who can combine deep algorithmic and backend engineering capabilities with a sharp focus on execution, delivery, and solving complex architectural challenges.

Reporting directly to Datonics CTO, you will play a central, high-impact role in shaping our core data pipelines, partner integrations, and proprietary audience graph solutions.

We work in a flexible hybrid model (2 days a week from our office).

What we are looking for:

• 5+ years of hands-on experience in Big Data / Data Engineering or Backend Engineering with a deep focus on large-scale data architectures.
• Proven track record of writing and optimizing complex queries and data models in Snowflake and/or Google BigQuery.
• High proficiency in Python (and/or Scala/Java) for data processing, automation, and API integrations.
• Hand On experience working with machine learning algorithms (specifically Lookalike/classification modeling) and building AI agents / LLM integrations for real-world production tasks.
• Background in AdTech - Advantage
• Self-directed mindset with the ability to lead technical tasks from scratch, architect solutions independently, and make sound technical decisions.
• Strong communication skills in English and Hebrew, with the ability to articulate technical tradeoffs clearly to cross-functional stakeholders.

What you'll be doing:

• Complex Data Querying & Graph Modeling:
• Author, optimize, and execute efficient, high-volume queries in Snowflake and Google BigQuery.
• Connect disparate graph dumps (households, consumer profiles, C2C linkages, and email histories) into robust hierarchical structures that mirror and enhance our graph service capabilities.
• Partner Integrations & Pipeline Architecture:
• Design, build, and maintain scalable, reliable, and secure data flows between external strategic partners and the Datonics ecosystem.
• Define and manage end-to-end data ingestion, transformation, and streaming mechanisms to support real-time and batch requirements.
• Applied AI & Agent Development:
• Architect, build, and deploy intelligent AI agents capable of ingesting web page URLs and classifying them into standardized IAB categories.
• Evaluate and integrate LLMs/ML models and prompt frameworks into automated, production-grade pipelines.
• Audience Modeling & Machine Learning:
• Leverage ML algorithms to build, optimize, and test scalable Lookalike audience segments derived from first-party (1P) data.
• Partner with internal stakeholders to translate product and business data requirements into high-performance algorithmic solutions.
• Technical Ownership & Best Practices:
• Set high standards for data quality, code review, testing, performance tuning, and technical documentation across all data initiatives.