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We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

This is a full-time on-site role for an AI Data Analyst, located in the Tel Aviv District, Israel. The AI Data Analyst will be responsible for analyzing data, developing data models, conducting statistical analysis, and communicating findings to relevant stakeholders. Daily tasks will include interpreting complex data sets, generating actionable insights through data analytics, and supporting the development of AI-powered compliance solutions.

We are looking for a passionate Data Scientist Team Lead to join our all-star team. This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, results, marketing and data-oriented environment.

You will become the focal point of our data team and streamline processes, and will be responsible over company revenue streams.



What Youll Do

Mentor a team of extremely talented and success-hungry data scientists.
Initiate and manage cutting-edge projects from inception to delivery, including developing structured and automated solutions.
Lead the data strategy: be responsible for planning, prioritizing, and building the right data solutions to support business needs.
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems.
Identify and propose data science and algorithmic solutions for various product initiatives.
Use your excellent communication skills, both written and verbal, to explain technical concepts and analysis implications to senior leaders, and influence cross-functional teams to improve performance.
Partner with other departments (i.e. Management, R&D, Product) to support decision making.

As our Senior Data Engineer you will handle Big Data in real time, and become the owner and gatekeeper of all data and data flows within the company. You will bring data ingenuity and technological excellence while gaining a deep business understanding.

This is an amazing opportunity to join a multi-disciplinary A-team while working in a fast-paced, modern-cloud, data-oriented environment.

Implement robust, reliable, and scalable data pipelines and data architecture.
Own and develop DWH (petabytes of data!).
Own the entire data development process, including business knowledge, methodology, quality assurance, and monitoring.
Collaborate with cross-functional teams to define, design, and ship new features.
Continuously discover, evaluate, and implement new technologies to maximize development efficiency.
Develop tailor-made solutions as part of our data pipelines.
Lead complex Big Data projects and build data platforms from scratch.
Work on high-scale, real-time, real-world, business-critical data stores and data endpoints.
Implement data profiling to identify anomalies and maintain data integrity.
Work in a results-driven, high-paced, rewarding environment.

As a Senior Data Scientist , you will be an integral part of our Machine Learning and AI team. The role is hands-on and impact-driven, focusing on building, improving, and delivering machine learning models that directly support business goals.

Responsibilities
Design and deploy production ML systems that drive automated business decisions (pricing, bidding, resource allocation)
Build end-to-end ML pipelines - from data ingestion and model training to serving, monitoring, and incident response
Translate ambiguous business problems into rigorous mathematical frameworks and own them from conception to production impact
Conduct rigorous experimentation (A/B testing, causal inference, uplift modeling) to measure and improve model performance
Maintain and improve real-time models that adapt to incoming data and feedback signals
Mentor junior team members on ML best practices and production standards

we are seeking a Senior Data Analyst position to join the BI Team, with a passion for technology, to solve unique problems within our measurements. Our team solves many challenges in turning raw data into accurate signals and extracting insights to improve the 365Scores products. Appropriate candidates have an understanding of multiple components across the big data stack: large-scale data analysis, data quality, statistics, and visualization. If you are the kind of researcher who's focused on results and a quick learner, this role is for you. This position is located in our Tel Aviv office.

Responsibilities
Function as the data authority in the Monetization domain - performing ad-hoc research and analysis on the company's rich data to support unique and strategic business questions.
Define, analyze, and monitor KPIs and OKR metrics to continually improve company products.
Analyze large, complex data sets to address strategic and operational business questions.
Actively take part in building and maintaining our AI Driven-BI Agentic Architecture.
Build dashboards and visualizations to answer key questions for the company's in-house various teams, specifically for the Monetization Team.
Perform qualitative, quantitative, and statistical analysis.
True passion for understanding data and finding Insights.
Provide actionable recommendations and conclusions from data to shape features and future product road maps.

Required Data Engineer
About The Position
Design, build, and maintain scalable data pipelines and infrastructure entirely within GCP
Own data solutions end-to-end, from architecture and design through to production delivery
Build and maintain custom connectors to advertising platforms including Google Ads, Meta (Facebook) Marketing API, and other ad platforms
Design and implement data warehouse structures with a deep focus on performance, scalability and usability
Continuously investigate and evaluate new GCP native tools and services, assessing their fit, building proof of concepts, and driving adoption where it makes sense
Set up and configure orchestration and transformation frameworks (such as Airflow and dbt) within the GCP environment
Collaborate closely with backend engineers to ensure data infrastructure aligns with product and system needs
Contribute to data science initiatives and bring genuine curiosity to analytical use cases
Monitor, troubleshoot, and continuously improve the reliability and performance of existing data systems
Define technical standards and best practices for the data platform
Build and maintain data dashboards and reports to surface insights for stakeholders, primarily using Looker Studio.

As a Data Scientist, you will be responsible for the entire algorithmic lifecycle of our company's solution. From analyzing large scale customer data to shipping new models to production, your responsibilities will be end-to-end.
Mentoring and coaching team members is an essential aspect of your position.
The role is a hybrid work model from our offices in Tel Aviv.
Key Responsibilities
Collaborate with the product team and occasionally engage with customers to gather requirements for developing and delivering new predictive solutions.
Analyze large volumes of diverse data sets and develop algorithmic solutions and models to solve complex problems.
Turn algorithm prototypes into shippable products that have a significant and immediate impact on our company's success.
Collaborate with software engineers to develop scalable solutions.
Take end-to-end ownership of projects and ensure successful delivery.
Continuously improve our tech stack and development practices.
Mentor and coach team members as a domain expert.

As a AI-Data Engineer, youll take a leading role in building the foundation of our companys Agentic Exposure Management platform: the source of truth that tells a security team what they have, whats actually risky and why, how to fix it, and who is responsible.
Enterprises run their security across a sprawl of cloud and on-prem tools. Making sense of that sprawl is the heart of what we do. Were building a complex data fabric that reconciles data from a hundred different sources, applies sophisticated transformation and enrichment, and turns partial, uncertain signal into one trustworthy model of an organizations real exposure.
Key Responsibilities:
Model the security graph. Design an ontology that spans both the modern cloud and the classical on-prem world, abstract enough to absorb 100+ different integrations under one model, yet rich enough to carry everything needed for decision making. Decide whats an entity, whats an edge, and whats a denormalized attribute, across millions of assets and finding rows.
Own asset identity engineering and reconciliation. Upstream identifiers are uncertain and volatile. Engineer deterministic identity resolution for assets and findings arriving from different vendors.
Build LLM-based and agentic pipelines for data classification, entity extraction, and enrichment, optimizing for cost, latency, and precision in production.
Build the integration factory. Stand up a scalable integration platform that drives down time-to-integration.
Build and maintain complex ETL pipelines handling millions of records: incremental sync, complex correlation, and data quality observability and monitoring.

We are seeking a visionary and hands-on Staff AI Scientist to help shape the next generation of foundational language models and agentic systems that empower small and medium-sized businesses to thrive. In this role you will define, design, and build groundbreaking AI solutions that understand, reason, and act across complex financial and business contexts.
You will collaborate closely with cross-functional experts across AI research, data science, engineering, and product to create intelligent agents that help SMBs automate financial tasks, make smarter decisions, and operate more efficiently. Your work will combine scientific rigor with visionary execution, balancing theoretical innovation with large-scale practical impact.
As a Staff Scientist you set technical direction beyond your own projects. You are a builder-scientist - a creative thinker who develops novel model architectures and training paradigms and also drives their implementation and validation in real-world applications - and you raise the scientific bar for the teams around you. You will help shape the AI foundation that powers transformative products serving millions of customers.
Responsibilities:
Set technical direction. Define the technical strategy and roadmap for next-generation agentic and foundation-model systems, and drive innovation and scientific excellence across the organization.
Build foundational models and agents. Design and develop foundational language models and agentic architectures that power intelligent decision-making for small and medium businesses.
Advance the science. Explore novel approaches in large-scale pretraining, fine-tuning (SFT and RLFT/GRPO), retrieval-augmented generation, and reasoning to improve factuality, adaptability, and alignment.
Solve real financial work. Build intelligent agents that understand financial data, customer context, and business workflows - from bookkeeping and autonomous accounting to planning, communication, and insight generation.
Leverage our data moat. Turn our unique ecosystem signals - counterparty behavior, two-sided transaction visibility, and business twins - into defensible modeling advantages.
Ship end-to-end. Take work from experimentation to production, owning evaluation frameworks and metrics that prove real-world impact.
Elevate others. Mentor scientists and engineers, review technical designs, and grow the craft of the wider team - a core expectation at the Staff level.
Collaborate across functions. Partner with AI research, engineering, product, and design to translate breakthrough science into scalable products used by millions.
Share knowledge. Publish and present research findings, internal innovations, or contributions to open-source frameworks where appropriate.

We are seeking a highly skilled and analytical Senior Data Engineer to join our Data team. In this role, you will design and implement robust data pipelines, while uniquely bridging the gap between engineering and analytics by actively analyzing data to extract actionable insights. You will play a crucial part in architecting our data foundations to support everything from business intelligence to advanced machine learning and agentic AI pipelines.
As a Senior Data Engineer, you will collaborate closely with engineering teams, product managers, and stakeholders across the organization. You will not only build the infrastructure utilizing modern data stack tools but also act as a data analyst when needed, ensuring our systems are fully equipped to operate within and support a cutting-edge agentic AI environment.
Responsibilities
Design, build, and maintain highly scalable ELT/ETL data pipelines.
Architect and manage modern cloud data warehousing solutions.
Develop, maintain, and monitor Python services responsible for robust data collection and ingestion.
Perform hands-on data analysis to interpret complex datasets, identify trends, and deliver business insights, acting in a dual capacity as a Data Analyst.
Develop and optimize data infrastructure specifically designed to support autonomous agentic workflows and LLM integrations.
Collaborate with engineers and analysts to troubleshoot data issues, enforce quality SLAs, and define data requirements.
Document data architecture, flow, and analytics standards for internal team alignment.
Build and maintain dashboards and reports to communicate analytical findings and data health to the organization.
Maintain Kafka consumer applications that process high-volume event streams in real-time, ensuring reliable ingestion into cloud databases.

We built a platform that builds businesses. From launching and managing to growing a business, we are the all-in-one solution that empowers any business owner. Our platform services over 40 million small businesses. Our "Guidance Engine" assesses each new business introduced to our platform and devises a tailored plan that allows you to manage all your business needs from a single dashboard. Through our business-building platform, were turning the process of starting, managing, and growing a business into a better experience; were simplifying the business journey. At Tailor Brands, we believe in more than just handing you another tool; we are dedicated to teaching you the art of building a business.
About the Role:
As a data Engineer, you'll design and maintain the data pipelines that power decision-making across product, marketing, and finance. Working with Apache Airflow, Python, and SQL, you'll build trusted, well-documented datasets that enable self-service analytics for the entire organization. You'll champion data quality through validation and monitoring, optimize infrastructure for scale, and be part of a forward-thinking team that actively leverages AI tools like Claude to push the boundaries of modern data engineering. If you thrive on turning messy data into reliable, actionable foundations - and want to do it for a platform serving over 40 million small businesses - this role is for you. What were looking for:
* Design, implement and maintain pipelines that deliver data with measurable quality and SLAs for our product, marketing, finance, and other departments
* Partner with business domain experts, data analysts, and engineering teams to build foundational datasets that are trusted, well-understood, aligned with business strategy and enable a self-service analysis
* Focus on data quality, detect data /analytics quality issues, implement bug fixes and data validations for prevention
* Identify, design, and implement internal process improvements such as automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc
* Be part of a team that actively integrates AI tools like Claude into day-to-day workflows, pushing the boundaries of how data engineering gets done

As a Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.


Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

As a Senior Data Engineer, youll collaborate with top-notch engineers and data scientists to elevate our platform to the next level and deliver exceptional user experiences. Your primary focus will be on the data engineering aspects-ensuring the seamless flow of high-quality, relevant data to train and optimize content models, including GenAI foundation models, supervised fine-tuning, and more.

Youll work closely with teams across the company to ensure the availability of high-quality data from ML platforms, powering decisions across all departments. With access to petabytes of data through MySQL, Snowflake, Cassandra, S3, and other platforms, your challenge will be to ensure that this data is applied even more effectively to support business decisions, train and monitor ML models and improve our products.



Key Job Responsibilities and Duties:

Rapidly developing next-generation scalable, flexible, and high-performance data pipelines.

Dealing with massive textual sources to train GenAI foundation models.

Solving issues with data and data pipelines, prioritizing based on customer impact.

End-to-end ownership of data quality in our core datasets and data pipelines.

Experimenting with new tools and technologies to meet business requirements regarding performance, scaling, and data quality.

Providing tools that improve Data Quality company-wide, specifically for ML scientists.

Providing self-organizing tools that help the analytics community discover data, assess quality, explore usage, and find peers with relevant expertise.

Acting as an intermediary for problems, with both technical and non-technical audiences.

Promote and drive impactful and innovative engineering solutions

Technical, behavioral and interpersonal competence advancement via on-the-job opportunities, experimental projects, hackathons, conferences, and active community participation

Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.

Were looking for a Technical Integration Manager to join our team and help connect the dots between our business goals and R&D efforts. This hybrid role is ideal for someone who enjoys working between business and technology, combining project coordination with technical understanding.
Youll be the main connection between our business units and R&D - understanding business needs, translating them into clear requirements, aligning priorities, and helping teams deliver successfully. Youll also support product and project activities to move initiatives forward.

Responsibilities

Serve as the main point of contact between business stakeholders and R&D
Translate business needs into clear requirements and technical briefs
Work closely with R&D to ensure alignment on scope, timelines, and delivery expectations
Own development initiatives end-to-end spec, tasks, QA, rollout, and monitoring whether you build them yourself using AI tools, automation and no-code, or hand them to R&D developers.
Write technical specs and acceptance criteria, and manage the work in task management tools.
Guide and train the business departments on new features documentation, walkthroughs, and ongoing support
Coordinate cross-functional meetings, updates, and ongoing communication
Assist in planning and prioritizing roadmaps and project timelines
Track and report on progress, risks, and blockers across multiple initiatives
Solve complex tech problems and support the business departments
Build new dashboards for internal and external users using tools like Google Data Studio, Redash, Tableau and others.