Were looking for a Senior Data Engineer to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isnt a pure infrastructure role - youll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.
You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. Youll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.
This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.
Key Responsibilities
Act as a technical leader within the team - raise engineering standards, drive strong architectural choices, and improve how we build
Own data products end-to-end: design, development, deployment, monitoring, and iteration
Work closely with senior leadership to translate strategic goals into scalable data solutions
Develop and maintain production ETL/ELT pipelines using DBT (on Spark) and orchestrated workflows in Databricks
Build monitoring, alerting, and testing pipelines to ensure reliability and performance in production
Evaluate and introduce new technologies - including AI-native development tools - and integrate the ones that create real impact
Collaborate with customers and external data providers - gathering requirements and making product decisions.
Mentor team members through code reviews, pairing, and knowledge sharing

we are looking for a Data Infrastructure Engineer.
Responsibilities:
Design and build data solutions that support core business goals, from enabling capital market transactions (loan sales and securitization) to providing
reliable insights for reducing the cost of capital.
Develop advanced data pipelines and analytics to support finance, accounting, and product growth initiatives.
Create ELT processes and SQL queries to bring data to the data warehouse and other data sources.
Develop data-driven finance products that accelerate funding capabilities and automate accounting reconciliations.
Own and evolve data lake pipelines, maintenance, schema management, and improvements.
Create new features from scratch, enhance existing features, and optimize existing functionality.
Collaborate with stakeholders across Finance, Product, Backend Engineering, and Data Science to align technical work with business outcomes.
Implement new tools and modern development approaches that improve both scalability and business agility.
Ensure adherence to coding best practices and development of reusable code.
Constantly monitor the data platform and make recommendations to enhance architecture, performance, and cost efficiency.

We are looking for a hands-on Data Engineer to join engineering team and take ownership of core data processes within one of our product teams.

You will design and maintain reliable ETL pipelines, connect to external data sources, and help build scalable data foundations for product features, analytics, and AI-driven capabilities. This is a great opportunity to own meaningful data processes end-to-end and work closely with product, engineering, and data stakeholders.


Your Ownership Will Include

Design, build, and maintain end-to-end ETL pipelines for production use.
Work with large-scale cloud usage data from different sources and formats.
Build data flows using Apache Spark and Databricks or similar technologies.
Structure data using Data Lake / Lakehouse concepts, including Bronze, Silver, and Gold layers.
Integrate with external APIs and data sources.
Prepare and model data for product features, analytics, and AI-related capabilities.
Ensure data quality, reliability, and observability across pipelines.
Collaborate closely with backend engineers, data analysts, and product stakeholders.

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.

Director, Business Intelligence & AI to join our Business Applications organization. This is a senior individual contributor role with a director title and light team leadership (5 people), sitting at the intersection of data strategy, architecture, and execution. You'll own the data foundation that powers our company's most critical business decisions - from GTM and revenue analytics to operational intelligence across the organization.

You'll report to the VP of Business Applications and work closely with stakeholders across Finance, Sales, Marketing, Customer Support, Product, R&D, and HR to ensure our data assets are trustworthy, scalable, and increasingly AI-ready



What will you do?

Architecting the data foundation that makes it possible for business users to ask questions in plain English and get trusted, real-time answers.
Define and execute a strategy to migrate from traditional BI (dashboards, scheduled reports) toward AI-powered, natural language interfaces for business intelligence
Architect the data layer that enables LLM-based querying - including semantic layers, vector stores, knowledge graphs, and metadata enrichment - so that AI agents can reliably reason over company data
Design and own a scalable, AI-ready data architecture - warehouse/lakehouse structure, semantic layer, and data contracts - that supports both analytical and AI/ML workloads
Build robust data modeling foundations (clean entities, clear metrics definitions, consistent taxonomies) that LLMs can reason over accurately
Serve as a trusted advisor to business leaders across GTM, Customer Success, Finance, and Product - proactively engaging them to understand their decision-making needs
Translate ambiguous business questions ("why is churn spiking in the mid-market?") into well-defined data problems, and then into scalable, AI-powered solutions
Build strong relationships with stakeholders at all levels - from individual analysts to VP and C-suite - and maintain a prioritized roadmap that reflects real business value

Required Software & Data Engineer
Tel Aviv
We are on a mission to create public transportation systems that provide far greater access to jobs, healthcare, and education. Our platform serves as the technology backbone for modern transit networks, transforming antiquated and siloed public transportation systems into smart, data-driven, and efficient digital networks. With hundreds of agency partners around the world, we are recognized as the leading transportation technology and service provider globally.
As a Software & Data Engineer, you will play a central role in building and evolving the data infrastructure that powers one of the world's leading transportation platforms. You'll work with rich, complex transportation data - from ride bookings and payments to real-time operational signals - designing the pipelines and systems that turn raw data into clean, reliable, and actionable insight across the business. This is a high-ownership role on a talented and deeply motivated engineering team in Tel Aviv, where your work will directly shape how we understand and improve our service for cities and riders around the world.
About the Role:
Design and build highly scalable, reliable data pipelines that serve clean, structured data across our engineering, product, and business teams - ensuring the entire organisation can trust the data it works with
Own the architecture of complex data models that translate messy, real-world transportation data - bookings, payments, driver activity, and more - into systems that are fast, efficient, and built to scale
Lead end-to-end development across the full data lifecycle: from architecture and design through to deployment, monitoring, and continuous improvement
Proactively monitor data quality and reliability, identifying and resolving discrepancies before they reach stakeholders - building the kind of data infrastructure people can depend on
Collaborate with a broad forum of engineers, analysts, and business stakeholders to identify data needs, design POCs, and ship scalable solutions that make a real difference to how we operate
Contribute to the adoption and evolution of our modern data stack, including DBT, Airflow, Iceberg storage, and AWS big data tooling such as Glue, EMR, and Athena.

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.

The leading global financial news & data platform, is on the lookout for a Senior Data Engineer to join our growing data team!
In this role, you will design and develop scalable data solutions, optimize data workflows, and support critical business processes. You will work with a variety of databases and big data tools in a cloud environment, focusing on data modeling, governance, and analytics.
What youll be doing:
Design, develop, and maintain end-to-end ETL pipelines, from gathering business requirements to implementation.
Work with multiple database technologies, especially BigQuery.
Optimize data models (DWH, fact & dimension tables, RI, SCDs) for performance and scalability.
Implement data governance best practices and maintain comprehensive documentation.
Utilize Big Data tools in cloud environments (GCP preferred).
Develop and support complex business workflows and data processes.
Design and implement monitoring systems to ensure data quality throughout the pipeline.
Workflow orchestration using Apache Airflow.
Collaborate with analysts and stakeholders to ensure high-quality data for business insights.
Support and optimize Tableau infrastructure for data visualization.

Were looking for a Senior Data & Analytics Architect to join our team and work directly with startup CTOs, engineering teams, and account teams. This is a hands-on, customer-facing architecture role where you will design and deliver production-grade data platforms on AWS.

The role is focused on turning real business problems into working systems, from early discovery and architecture design to supporting implementation. This is not a pure strategy or management role, its about making clear technical decisions and ensuring they hold up in production.

Work location: hybrid from Tel Aviv.

If you are interested in this opportunity, please submit your CV in English.

Key Responsibilities:
Design and deliver end-to-end data platforms on AWS, covering ingestion, storage, processing, and serving layers, including Well-Architected reviews and contribution to SOWs and HLDs.
Work directly with startup customers to understand requirements, challenge assumptions, and shape practical solutions.
Lead technical discussions, workshops, architecture reviews, and POCs.
Translate ideas and early concepts into clear architectures, including HLDs, SOWs, and implementation direction.
Make and explain trade-offs across cost, performance, scalability, and complexity.
Stay close to delivery, supporting teams to ensure solutions are implemented correctly.
Collaborate with Data Engineers, DevOps, Solution Architects and Account Managers to move projects from concept to production.
Contribute to internal standards, reusable patterns, and reference architectures.
Operate in a fast-paced, project-based environment with multiple customer engagements.
Stay up to date with modern Data Engineering and Analytics practices, and contribute to internal enablement, patterns, and knowledge sharing.
Work in a customer-facing environment that includes occasional travel, both locally for meetings and events, and internationally around once per quarter.