דרושים » דאטה » Backend Engineer, Data Foundations

We are disrupting the multi-trillion dollar transportation industry with our advanced Customer data Platform (CDP). Our work happens in the fast lane as we bring AI-powered, data -driven solutions to a quickly evolving industry. Our team is made up of curious and creative individuals who are always looking to achieve the impossible. We are bold, collaborative, and goal driven, and, at our core, we believe every voice has value and can impact our bottom line. If you are a creative, solutions oriented individual who is ready to put your career in drive, we are the place for you! We are looking for Senior Engineers who treat AI as a core part of their workflow - people who experiment, iterate, and know how to get real value out of AI tools. Flexibility, curiosity, and a problem-solving mindset are must-haves. In this role you will have the opportunity to take ownership of the development of groundbreaking, AI-driven products and work on interesting projects inside a smart, fun, and dynamic engineering team. This position is based out of our Jerusalem or Tel-Aviv offices and reports to the Dev team lead.

What you will be responsible for:
* Write clean, high-quality, high-performance, maintainable code.
* Ensure that the projects you work on meet business objectives and coding standards.
* Support the deployment and testing of new products and features.
* Collaborate with cross-functional teams to gather and analyze requirements, translating them into technical specifications.
* Design and implement APIs and integrations with third-party services to enhance system functionality.
* Optimize application performance through code profiling, monitoring, and refactoring as necessary.
* Implement automated testing frameworks to ensure code robustness and reliability.
* Participate in code reviews and provide constructive feedback to peers to foster continuous improvement.
* Stay updated with emerging technologies, best practices, and industry trends to drive innovation within the team.
* Assist in the establishment and enforcement of development standards and coding conventions.

Why you should join us:

* An awesome global team of forward-thinking, innovative go-getters
* Integrate with tech titans: Work directly with APIs from Google, facebook, Microsoft, and more.
* Be part of a rapidly scaling company poised for the future.
* Learning and growth opportunities within a fast-paced SaaS startup environment
* Clear career advancement path for strong performers
* As a part of our team, your success in this role is crucial to our company's growth. We are committed to supporting you in achieving your KPIs and goals and providing regular feedback to help you reach your full potential. Together, we can make a real impact and achieve great things!
* And how can we forget? Cibus and lots of yummy kitchen treats:-) In the meantime, you can get to know us a little better by checking out  on instagram facebook LinkedIn Are you the one? Send your resume to us

Required Data Engineer
Working in data is about finding what nobody else knew they lost. We want investigators, people who adapt, think flexibly, and know how to bring leadership onboard. From scientists to engineers to visualization experts, our data team is made for those who find the missing piece and act on it. So if curiosity is your default setting and making it useful your priority, the Data team might be what you're looking for.
Join our dynamic Data department as a Senior Data Engineer, where you'll play a pivotal role in launching a critical new data product. This is an opportunity to elevate our engineering rigor and deliver innovative solutions for the world's most popular freelance marketplace, tackling complex challenges with advanced data warehousing and full-stack development expertise.
What am I going to do?
Architect and design robust schemas for our new data product backend, ensuring scalability and performance.
Drive full-stack feature development for production-ready features, contributing to both data pipelines and user-facing elements.
Orchestrate and optimize data pipelines, guaranteeing reliable and timely data delivery.
Provide technical leadership to enhance software engineering standards across the team, mentoring other developers.
Integrate complex systems and manage schema design with a keen eye on cost optimization.
Collaborate closely with cross-functional teams in daily stand-ups and development cycles.

Were looking for a Data Engineer to join our company. This is a hands-on, cross-functional role focused on owning and improving our data quality, pipeline reliability, and modeling infrastructure. Youll be responsible for managing and optimizing our DBT models, ETL processes, and data connectors - and will work closely with product, operations, and engineering teams to ensure data is accurate, consistent, and accessible.

You should be someone who thrives on autonomy, takes pride in clean and scalable solutions, and enjoys helping others get the data they need.

In this role you will
Architect our entire DBT project and data warehouse structure completely from scratch-a rare, high-impact opportunity
Lead data modeling efforts: Translating business needs into scalable, reliable data models
Build and monitor data pipelines and connectors from various internal and external systems
Ensure high standards of data quality, consistency, and documentation
Collaborate with engineering, product, and operations teams to understand needs and build data solutions
Proactively detect data issues and work to resolve them
Help define and improve internal data best practices and standards
Support data governance efforts and advocate for trustworthy, well-modeled data
You will be one of the pioneers of a new team - passion & energy is required

Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.

So, what will you be doing all day?

Your role as Data Engineer of the Ingest Data Collection team means your daily responsibilities may include:

Design, code and manage end-to-end data ingestion pipelines, both online and offline.
Take charge of developing & maintaining modern data infrastructure, while implementing best practices for building data pipelines.
Be responsible for high-scale ingestion services, solving challenges of availability, reliability, and scalability.
Run the production environment by monitoring availability and taking a holistic view of system health and data quality.
Own data infrastructure features from design to production using industry best practices with focus on quality and delivery.
Lead design & decision-making processes of the team.
Solve diverse complex problems of scale, performance and business logic.
Collaborate with product managers and other team leaders to plan, nurture, and implement an efficient and effective development process.
Continuously learn and evaluate new technologies in the everlasting effort to perfect our products
Perform code reviews, evaluate implementations, and provide feedback about potential improvements.
Improve your skills, learn from and mentor top-notch engineers and enrich other team members.
Have lots of fun!

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across .
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build next-generation data stack.
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 you'll
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals

We are looking for an experienced and visionary Data Engineer to help design, build, and scale our BI platform.
In this role, you will be responsible for developing our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics to provide insights that serve both business intelligence and product needs.
You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.
If you enjoy turning raw data into powerful insights and owning the full data lifecycle, this role is for you!
Responsibilities
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability, and security.
Design and architect data products, from ingestion to transformation, modeling, storage, and access.
Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.
Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.
Integrate modern tools and frameworks such as Airflow, Databricks, Power BI, and streaming platforms.
Collaborate cross-functional with product, engineering, and analytics teams to translate business needs into data infrastructure.
Promote a data-driven culture - be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

Req ID: 21679

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.

Req ID: 20718

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.

Were looking for a BI & Data Engineering Team Lead to join our BI team and take end-to-end ownership of high-impact analytics foundations while mentoring a team of 4-6 talented BI Data Engineers. This role sits at the core of how measures success, makes decisions, and scales-turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.

In this role, you'll combine people leadership with hands-on technical depth (roughly 30% of your time), owning the roadmap, architecture, and delivery of BI platform. Youll shape how AI and agentic workflows transform the way BI is built and consumed, helping raise the bar for analytics engineering across the company.

Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.

This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.

This might be for you if:

You enjoy owning data foundations end to end - from raw data to semantic layers while leading and growing people
You like turning ambiguous business questions into clear, governed metrics and scalable data models
You care about data quality, performance, and trust at scale, as well as optimization and FinOps practices
You enjoy mentoring, setting technical standards, and leading by example with a hands-on approach (~30%)
You actively leverage AI tools and agentic automations to improve development speed, analytical accuracy, and metric governance

As a Senior Data Engineer , you will play a key role in building and scaling the companys data infrastructure. Youll be responsible for creating the foundation that enables teams across the organization to access, analyze, and leverage data effectively. Working closely with Data Science, Delivery, Product, GTM, and Analytics teams, youll design and maintain data pipelines, manage our data warehouse, and transform raw data into structured, reliable assets that power business and product decisions.



What Youll Do

Build and Manage Data Infrastructure: Own and maintain Nomas data warehouse infrastructure, ensuring scalability, reliability, and performance
Develop Data Pipelines: Design, build, and maintain data pipelines that transform company data into structured, queryable assets
Enable Data-Driven Decisions: Partner with Engineering, Data Science, Product and Analytics teams to deliver trusted data foundations and actionable insights.
Create BI Dashboards: Build and maintain dashboards and reporting layers that support product, and operational decision-making
Ensure Data Quality and Accessibility: Implement best practices for data modeling, governance, monitoring, and reliability