לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בתל אביב יפו

we are Crafting Tomorrow's Retail Experience
We started with a simple question: How can vision AI make shopping better for everyone? Today, our team of passionate experts is transforming how people shop and how retailers operate, one store at a time.
Our goal is to solve real retail challenges by developing advanced computer vision AI that prevents loss, enables grab-and-go shopping, and turns store data into valuable insights, all while delivering clear value from day one.
With multiple global deployments, deep partnerships with leading retailers, and a product suite thats proving its impact every day, our company isnt just imagining the future of retail, were building it.
We are looking for a Data Engineer to join our Customer Performance team and help shape the foundation of our companys data platform.
You will own the data layer, evolve our BI semantic layer on a modern BI platform, and enable teams across the company to access and trust their data. Working closely with analysts and stakeholders in Operations, Product, R&D, and Customer Success, youll turn complex data into insights that drive performance and customer value.
A day in the life
Build and expand our companys analytics data stack
Design and maintain curated data models that power self-service analytics and dashboards
Develop and own the BI semantic layer on a modern BI platform
Collaborate with analysts to define core metrics, KPIs, and shared business logic
Partner with Operations, R&D, Product, and Customer Success teams to translate business questions into scalable data solutions
Ensure data quality, observability, and documentation across datasets and pipelines
Support complex investigations and ad-hoc analyses that drive customer and operational excellence.

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

Your Mission As a Senior Data Engineer, your mission is to build the scalable, reliable data foundation that empowers us to make data-driven decisions. You will serve as a bridge between complex business needs and technical implementation, translating raw data into high-value assets. You will own the entire data lifecycle-from ingestion to insight-ensuring that our analytics infrastructure scales as fast as our business.

Key Responsibilities:
Strategic Data Modeling: Translate complex business requirements into efficient, scalable data models and schemas. You will design the logic that turns raw events into actionable business intelligence.
Pipeline Architecture: Design, implement, and maintain resilient data pipelines that serve multiple business domains. You will ensure data flows reliably, securely, and with low latency across our ecosystem.
End-to-End Ownership: Own the data development lifecycle completely-from architectural design and testing to deployment, maintenance, and observability.
Cross-Functional Partnership: Partner closely with Data Analysts, Data Scientists, and Software Engineers to deliver end-to-end data solutions.

Are you a talented and experienced Data Engineer? If so, we want you to be part of our dynamic Data Engineering Team, a part of the R&D, contributing to our vision and making a difference in the eCommerce landscape. Join us on this journey as we seek the best and brightest minds to drive our mission forward.

Responsibilities:
Developing, implementing and supporting robust, scalable solutions to improve business analysis capabilities.
Managing data pipelines from multiple sources, including designing, implementing, and maintaining.
Translating business priorities into data models by working with business analysts and product analysts.
Collaborate across the business with various stakeholders, such as data developers, systems analysts, data scientists and software engineers.
Owning the entire data development process, including business knowledge, methodology, quality assurance, and maintenance.
Work independently while considering all functional and non-functional aspects and provide high quality and robust infrastructures to the organization.

We are looking for a Data Engineer to join our growing team!
This is a great opportunity to be part of one of the fastest-growing infrastructure companies in history, an organization that is in the center of the hurricane being created by the revolution in artificial intelligence.
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

Required Senior Data Engineer
About us:
A pioneering health-tech startup on a mission to revolutionize weight loss and well-being. Our innovative metabolic measurement device provides users with a comprehensive understanding of their metabolism, empowering them with personalized, data-driven insights to make informed lifestyle choices.
Data is at the core of everything we do. We collect and analyze vast amounts of user data from our device and app to provide personalized recommendations, enhance our product, and drive advancements in metabolic health research. As we continue to scale, our data infrastructure is crucial to our success and our ability to empower our users.
About the Role:
As a Senior Data Engineer, youll be more than just a coder - youll be the architect of our data ecosystem. Were looking for someone who can design scalable, future-proof data pipelines and connect the dots between DevOps, backend engineers, data scientists, and analysts.
Youll lead the design, build, and optimization of our data infrastructure, from real-time ingestion to supporting machine learning operations. Every choice you make will be data-driven and cost-conscious, ensuring efficiency and impact across the company.
Beyond engineering, youll be a strategic partner and problem-solver, sometimes diving into advanced analysis or data science tasks. Your work will directly shape how we deliver innovative solutions and support our growth at scale.
Responsibilities:
Design and Build Data Pipelines: Architect, build, and maintain our end-to-end data pipeline infrastructure to ensure it is scalable, reliable, and efficient.
Optimize Data Infrastructure: Manage and improve the performance and cost-effectiveness of our data systems, with a specific focus on optimizing pipelines and usage within our Snowflake data warehouse. This includes implementing FinOps best practices to monitor, analyze, and control our data-related cloud costs.
Enable Machine Learning Operations (MLOps): Develop the foundational infrastructure to streamline the deployment, management, and monitoring of our machine learning models.
Support Data Quality: Optimize ETL processes to handle large volumes of data while ensuring data quality and integrity across all our data sources.
Collaborate and Support: Work closely with data analysts and data scientists to support complex analysis, build robust data models, and contribute to the development of data governance policies.

our company Security is one of the main pillars of our company's long-term strategy. We are pushing the boundaries of security analysis for both binaries and code, shifting left and delivering powerful capabilities to developers and DevOps teams. We are looking for an experienced Senior Database Engineer with deep PostgreSQL expertise and strong application-side awareness to join our DevOps organization and support multiple R&D teams at scale.
As a Senior Database Engineer at our company Security you will
Own PostgreSQL performance, scalability, and reliability across large-scale security and scanning workloads
Deep dive into database performance issues, including query optimization, execution plans, indexing strategies, locking, bloat, vacuuming, and connection management
Work closely with application teams to optimize database access patterns from services and APIs
Review application code and SQL usage with a focus on correctness, performance, and scalability
Design, evolve, and optimize schemas and migrations for long-lived, high-volume datasets
Support and fine-tune PostgreSQL in both cloud-managed environments, such as RDS and self-managed deployments
Establish best practices, standards, and guidelines for PostgreSQL usage across teams
Mentor engineers and raise the overall database maturity of the organization
Act as a trusted expert for troubleshooting complex production database incidents.

we are looking for a DevOps Engineer (Data Platform Group).
Main responsibilities:
Data Architecture Direction: Provide strategic direction for our data architecture, selecting the appropriate componments for various tasks. Collaborate on requirements and make final decisions on system design and implementation.
Project Management: Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Cost Optimization: Monitor and optimize cloud costs associated with data infrastructure and processes.
Efficiency and Reliability: Design and build monitoring tools to ensure the efficiency, reliability, and performance of data processes and systems.
DevOps Integration: Implement and manage DevOps practices to streamline development and operations, focusing on infrastructure automation, continuous integration/continuous deployment (CI/CD) pipelines, containerization, orchestration, and infrastructure as code. Ensure scalable, reliable, and efficient deployment processes.
Our stack: Azure, GCP, Kubernetes, ArgoCD, Jenkins, Databricks, Snowflake, Airflow, RDBMS, Spark, Kafka, Micro-Services, bash, Python, SQL.

we are looking for a Senior Data Engineer.
Main responsibilities:
Provide the direction of our data architecture. Determine the right tools for the right jobs. We collaborate on the requirements and then you call the shots on what gets built.
Manage end-to-end execution of high-performance, large-scale data-driven projects, including design, implementation, and ongoing maintenance.
Optimize and monitor the team-related cloud costs.
Design and construct monitoring tools to ensure the efficiency and reliability of data processes.
Implement CI/CD for Data Workflows

We're seeking an outstanding and passionate Data Platform Engineer to join our growing R&D team.

You will work in an energetic startup environment following Agile concepts and methodologies. Joining the company at this unique and exciting stage in our growth journey creates an exceptional opportunity to take part in shaping our data infrastructure at the forefront of Fintech and AI.

What you'll do:

Design, build, and maintain scalable data pipelines and ETL processes for our financial data platform.

Develop and optimize data infrastructure to support real-time analytics and reporting.

Implement data governance, security, and privacy controls to ensure data quality and compliance.

Create and maintain documentation for data platforms and processes.

Collaborate with data scientists and analysts to deliver actionable insights to our customers.

Troubleshoot and resolve data infrastructure issues efficiently.

Monitor system performance and implement optimizations.

Stay current with emerging technologies and implement innovative solutions.

Were looking for a highly skilled Senior Database Engineer to join our DBA team. In this role, youll design and optimize our large-scale database infrastructure while ensuring high availability, scalability, and performance. In your day-to-day, you will:
Design and optimize our large-scale database infrastructure to meet high availability and performance standards
Identify cost-effective areas for improvement in current databases
Collaborate with developers and software architects to model, create, and maintain robust data structures and the data layer
Lead and execute technical database-related POCs and benchmarks
Conduct regular audits of database design to ensure quality and compliance with service level agreements (SLAs)
Quickly identify and resolve critical production issues and provide on-call support as needed.

Required Data Engineer - ML & GenAI Platform
Job Description
As a data engineer in our data science group, youll build, use, and enhance our ML and GenAI platforms, powering data products and LLM-based services across. Youll design and operate data and MLOps infrastructure for batch inference, knowledge-base workflows, evaluation metrics, and fine-tuning pipelines. Collaborating with data scientists, product managers, and engineers, youll bring AI features into production at scale.
Extend and implement new capabilities in ML and GenAI platforms
Design and maintain scalable, reliable data architectures and pipelines for model training, LLM fine-tuning, inference, and evaluation
Develop and maintain Airflow DAGs for metrics calculation, batch inference, KB workflows, and other data science projects
Collaborate with data scientists and engineers to integrate models and GenAI features into production systems Ensure high-quality code through best practices in testing, code reviews, documentation, and CI/CD for data and ML workloads
Work with tools and platforms like Airflow, Spark, Docker, Python Serverless, Kafka, and multiple cloud environments to deliver scalable, cost-effective GenAI solutions.

we are looking for a Senior Backend Developer.
What You'll Do:
Design and implement end-to-end features and services within a multi-service architecture.
Build and maintain a scalable data platform, incorporating advanced business logic and developing asynchronous, data-oriented, and scalable services.
Continuously improve and enhance the current data platform to ensure reliability, scalability, and performance.
Enhance and extend the functionality of existing systems.

It starts with you - an engineer who cares about building data pipelines and models that deliver reliable, trusted data. You value data quality, clean transformations, and making data accessible to those who need it. Youll work alongside experienced engineers to build ETL/ELT pipelines, maintain dimensional models, and implement quality checks that turn raw data into actionable intelligence.
If you want to grow your skills building data products for mission-critical AI, join mission - this role is for you.
:Responsibilities
Build and maintain ETL/ELT pipelines using platform tooling - workflows that extract from sources, apply transformations, and load into analytical stores.
Develop and maintain data models - fact/dimension tables, aggregations, and views that serve analytics and ML use cases.
Implement data quality checks - validation rules, tests, and monitoring for data freshness and accuracy.
Maintain documentation and lineage - keeping data catalogs current and helping consumers understand data sources and transformations.
Work with stakeholders to understand data requirements and implement requested data products.
Troubleshoot pipeline failures - investigating issues, fixing bugs, and improving reliability.
Write clean, tested, well-documented SQL and Python code.
Collaborate with Data Platform on tooling needs; work with Datastores on database requirements; partner with ML, Data Science, Analytics, Engineering, and Product teams on data needs.
Design retrieval-friendly data artifacts - RAG-supporting views, feature tables, and embedding pipelines - with attention to freshness and governance expectations.