לוח משרות דרושים הייטק דאטה בתל אביב יפו

One of the fastest-growing global D2C startups with a self-built e-commerce platform that allows us to leverage data and optimize marketing funnels to bring clinically tested body care products to women worldwide. With years of rapid growth and millions of customers worldwide. We are on track to become one of the biggest body care brands in the world. The company has built a strong tech backbone to leverage its data, collected over the span of dozens of million of $ in online advertising spend. The data analysis and predictive modeling guide the companys decision making and play a central role in its success, creating a unique competitive edge over the industry and other e-commerce players. We are a team of people who want to make lasting, impactful changes, who live (and love) to see results, who innovate with passion, and who love a good sense of humor. Is our vibe your vibe? We are currently looking for a logical and independent data Engineer to join its exceptional data Engineering Team. This cross-functional role works closely with analysts and the R&D team to support cross-departmental operations. The ideal candidate understands exactly how data structuring impacts macro-business decisions and can easily translate between technical and practical terms.
Your life will look like
* Create and structure end-to-end data pipelines and ETLs, ensuring analysts have the exact data they need to make smart, data -driven business decisions.
* Build scalable multi-step processes that integrate over 50 data sources, including Marketing, Operations, CS, Product, and CRM.
* Connect and leverage AI tools to build active business tools that drive critical company decisions.
* Proactively address data weaknesses while managing high-standard monitoring and reliability processes.

A part of the POC GROWING TEAM- This role will have a substantial impact on the company's future. It will involve managing the integration process with the data warehouses of some of the world's largest brands. This includes:

Mapping the different data sources to connect to (based on dozens of data sources Loops connects to).
Modelling the data in platform, based on the business context and the customers KPIs.
Building a deep understanding of Loops models and analyses to analyze them and debug problems.
Building and defining tools to automate and improve the integration process (scripts to automated data discovery, data pipeline, validation scripts, etc)
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Responsibilities
This is not a classic product analyst role:

Data is the underlying asset of our vision. You will directly impact the core value of the product, which is already used by major brands.
Youll be prioritizing and designing product features (not dashboards), yet you will also work closely with our customers to understand how data is leveraged to make decisions, learn which insights are valued, etc. This wide perspective will put you in a key position to shape the strategy of the growing product, and define its KPIs.
Model data within the platform based on business context and customer KPIs to deliver growth insights. This includes building and defining tools to automate and enhance the integration process, such as scripts for automated data discovery, data pipelines, and validation.
As part of the pre-sales department, you'll lead PoCs with top global companies. This diverse, fast-paced role offers exciting opportunities to work with various industries and make a significant impact. You play a key role in bridging customer needs to our solutions.
If youre interested, you will also have the opportunity of diving into the world of ML led by our excellent Data Science team, taking an active part in structuring the models which run behind our products engine.

We're seeking a Mid to Senior Data Engineer to join our Cloud Identity & Perimeter, a critical component of our security infrastructure. Our team develops and maintains complex data pipelines that process billions of records daily, analyzing identity-related security patterns, effective permissions, internet exposure, and attack paths. We're at the forefront of securing enterprise identities and delivering actionable security insights at scale.

What You'll Do:

Design and implement high-performance, distributed data processing pipelines handling petabytes of security data.

Architect complex data transformations using Apache Spark for large-scale batch and stream processing.

Be part of shaping new products while collaborating with product teams, customers, and sales.

Build and optimize real-time data streaming solutions using Kafka for identity analytics.

Develop and maintain scalable ETL processes that handle billions of daily events.

Create efficient data models for complex security analytics queries.

Collaborate with cross-functional teams to deliver high-impact security features.

Optimize query performance and data storage patterns for large-scale distributed systems.

Participate in system design discussions and architectural decisions.

This position is based in our Tel Aviv, Israel office and requires strong leadership presence and ability to work closely with cross-functional teams.

We are searching for a Senior Data Engineer to join our growing team in Tel Aviv and serve as a cornerstone of data evolution. We need an experienced, high-impact engineer ready to elevate our infrastructure from "functional" to "world-class."

As a pivotal member of the team, you wont just build pipelines; you will architect the future of our data ecosystem. Were looking for someone who obsesses over query latency, high-performance analytics, and cost-efficiency - someone who views data integrity as non-negotiable and thrives on turning complex event streams into elegant, scalable models.

Responsibilities
Lead the end-to-end data strategy, evolving our event-driven architecture to ensure seamless, low-latency data flow across the organization.
Design and implement robust, scalable data models that serve as the "single source of truth" for the entire organization.
Act as our internal Snowflake expert - optimizing performance and cost through best practices in clustering, materialized views, and warehouse management.
Build and maintain sophisticated ELT/ETL pipelines that transform raw event data into actionable insights, with a heavy focus on reliability and observability.
Proactively identify infrastructure bottlenecks and re-engineer processes to handle increasing scale without breaking a sweat.
Partner closely with Product and Engineering teams to translate business needs into technical reality, while mentoring analysts and peers on high-quality SQL and architectural standards.

Were looking for a talented Data Engineer to join our Data team and spread the power of our company. The Data team develops and maintains the infrastructure for internal data and product analytics. We are looking for data enthusiasts, independent, logical thinkers with a can-do approach and a passion for problem-solving. We run a SaaS-based stack using BigQuery, Snowflake and dbt.
WHAT YOU'LL DO
Design, build, and maintain data pipelines, datasets and catalogs for fast-growing products and business groups.
Develop self-service data analytics solutions and infrastructure.
Support ad hoc needs and requests of internal stakeholders.
Collaborate with analysts, engineers, and internal customers from Product, Finance, Revenue, and Marketing.

We are seeking a  Senior Data Scientist to join our Data Science team and lead the development of our 2D-to-3D modeling projects and help us bring the companys vision of virtual try-on to reality. The ideal candidate will have hands-on experience in 3D reconstruction, multi-view geometry, animation and neural rendering, with a proven ability to design and deploy production-ready models.
Responsibilities:
Lead research and development of 2D-to-3D modeling solutions, including single-image 3D reconstruction, multi-view 3D reconstruction, texture mapping, PBR mapping and depth estimation.
Own your deliverables from literature research, design and development to integration, testing and ongoing support
Collaborate with cross-functional teams to integrate research outcomes into scalable production systems.
Mentor other team members and promote teamwork
Continuously optimize team processes and workflows to improve efficiency and output

Were looking for a hands-on Technical Project Manager and spread the power of our company. As part of the CTO operations team, you will focuses on improving deployment pipelines and internal tools by digging into logs, finding recurring issues, and reducing manual work. The role combines technical problem-solving with practical execution and coordination.
WHAT YOULL DO
Youll work with engineers and domain leads to help teams improve how they build and operate systems.
Help build and maintain the Unified Maturity Table, defining the technical parameters (workflows, support packages, other metrics) and their KPIs that conclude a domains readiness and maturity.
Partner with the team to refine internal AI agents by measuring the performance of their answers against human expert interventions.
Use cluster analysis (AI) of support ticket descriptions to identify recurring patterns, then design and implement automated workflows to streamline resolution.
Take part in driving the departments "operating system" by facilitating design meetings, managing cross-domain syncs, and ensuring the documentation and support packages required for daily execution are current and actionable.
Define and implement different thresholds by analyzing support ticket complexity, resolution times, and domain-specific friction.
Transition static maturity reports into live, dynamic dashboards with trend lines.
Lead design meetings to establish cross-functional standards for domain maturity and system health alerts.

Required Data Engineer Position
I-Next Data Center, the AI Center is a pioneering data and research hub leading various initiatives to enhance medical diagnosis, prevention and treatment. Our projects encompass diverse areas, including decision-support applications for clinicians, predictive models, image processing, NLP and more.
We are seeking a highly motivated full-time data engineer who is enthusiastic about working with extensive clinical big data sources. The ideal candidate will be dedicated to creating and enhancing data processes to support our dynamic team.
Responsibilities
Conduct data extraction, validation and profiling to maximize the value of data
Design, implement, monitor and maintain data pipelines & ETLs for multiple data sources
Collaborate with researchers, experts and data scientists to comprehend data requirements as well as product design and deliver high-quality outcomes
Manage data development process, including methodology, QA and maintenance.

Required MDClone Engineer 
I-Next Data Center, the AI Center is a pioneering data and research hub leading various initiatives to enhance medical diagnosis, prevention and treatment. Our projects encompass diverse areas, including decision-support applications for clinicians, predictive models, image processing, NLP and more.
We are looking for a highly motivated full-time team member who is eager to work with clinical data. This individual will assist and guide clinicians and researchers in using a clinical data platform. In the future, they will also help improve data processes to enhance the platform further.
Responsibilities
Provide data-related services, support and guide clinicians ensuring their needs are met effectively
Collaborate closely with team members, fostering a cooperative and productive work environment.
Continuously learn and develop new skills independently to stay up to date in the data platform field.
Participate in team discussions and projects to enhance overall team performance and share knowledge.
Proactively identify opportunities for improvement and contribute to data platform development initiatives tailored to the healthcare member's sector.

SuperSonic is looking for a passionate Senior Data Scientist, to work end to end on some of our core problems. Solving these will help drive revenue and improve decision making.
As a Senior Data Scientist you will be handed a business problem and will be asked to provide an end to end solution - Unpack and thoroughly understand the business problem, define the strategy to deal with it and develop & deploy your solution along with relevant support.
What you'll be doing
Design and implement end-to-end solutions - from business needs all the way to live deployment
Monitor and own models in production
Model, design, and implement machine learning and data mining algorithms
Perform deep data analysis to evaluate performance and recommend improvements
Help, guide and support our business partners to allow for scale and accuracy while adopting your solutions.

Join a high-impact ML team building state-of-the-art systems that optimize experiences for billions of users. You'll tackle challenging problems across diverse datasets - with the freedom to explore novel approaches and infrastructure to deploy them at scale.
What Success Looks Like:
Short-term: Ship your first production model with measurable impact within 3 months.
Long-term: Own major ML initiatives end-to-end and introduce new methodologies that expand the team's capabilities.
Your Impact:
Elevate our technical bar with fresh ML perspectives. Shape our roadmap by identifying opportunities others miss. Your research skills keep us cutting-edge while your execution speed drives results.
What You'll Gain:
Work on real-time ML systems at scale with rich, diverse data
Autonomy to define problems and drive projects from idea to impact
Freedom to explore emerging techniques and expand your scope
Fast feedback loops through strong experimentation infrastructure
What you'll be doing
Join a high-impact ML team building state-of-the-art systems that optimize experiences for billions of users. You'll tackle challenging problems across diverse datasets - with the freedom to explore novel approaches and infrastructure to deploy them at scale.
What Success Looks Like:
Short-term: Ship your first production model with measurable impact within 3 months.
Long-term: Own major ML initiatives end-to-end and introduce new methodologies that expand the team's capabilities.
Your Impact:
Elevate our technical bar with fresh ML perspectives. Shape our roadmap by identifying opportunities others miss. Your research skills keep us cutting-edge while your execution speed drives results.
What You'll Gain:
Work on real-time ML systems at scale with rich, diverse data
Autonomy to define problems and drive projects from idea to impact
Freedom to explore emerging techniques and expand your scope
Fast feedback loops through strong experimentation infrastructure.

we are a data driven company, the data Engineering team is the bridge between raw data and impactful business insights. You will lead a team of talented engineers to architect, build, and maintain the data infrastructure of our company. Your mission is to ensure our data is reliable, secure, and ready for everything from standard BI reporting to cutting-edge Generative AI applications. Youll act as a key partner to our business teams, translating high-level needs into technical reality and driving a massive impact on our bottom line. In addition youll spend time mentoring your team as well as tackling high-level architecture decisions, pushing technical strategy and contributing to the codebase.
What am I going to do?:

* Lead a team that designs and scales Real-Time data pipelines processing millions of events hourly.
* Utilize cutting-edge technologies to build scalable and high performant data infrastructure.
* Influence and drive architecture and data strategy decisions.
* Work closely with other stakeholders such as data Developers, Analysts, data Science and R&D.
* Hands-on development of data infrastructure tools (~50% of the time).
* Lead and mentor the team talent.
* Finops and governance of data infrastructure domains.
Equal opportunities:
At our company, we prioritize diversity. We celebrate difference and embed it into every aspect of our workplace and product, as well as our community. we are proud and committed to providing equal opportunity employment to all individuals regardless of race, color, religion, sex, sexual orientation, citizenship, national origin, disability, Veteran status, or any other characteristic protected by law. In addition, we will provide accommodation to individuals with disabilities or a special need.

In your role as a Data Engineer , you'll be actively engaged in the most fascinating and demanding projects for our clients. Handling high-scale operations, heavy traffic, stringent SLAs, and massive data volumes is just the starting point. Our leadership in the realms of Big Data, Streaming Data, and Complex Event Processing (CEP) stems from our adept use of cutting-edge, optimal technologies.
Responsibilities:
Apply software-engineering methods and best practices (Medallion Architecture) in Data Lake management, using tools like DBT.
Develop Data pipelines to ingest and transform data.
Manage and enhance orchestrated pipelines across company
Data Modeling: Developing data models to ensure efficient storage, retrieval, and processing of data, often involving schema design for NoSQL databases, data lakes, and data warehouses. This will also include catalogs of data.
Scalability: Ensuring that the big data architecture can scale horizontally to handle large volumes of data and high traffic loads.
Data Security: Implementing security measures to protect sensitive data, including encryption, access controls, and data masking.
Data Governance: Establishing data governance policies to ensure data quality, compliance with regulations, and data lineage.

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.