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לפני 4 שעות
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Grip Security is looking for a Senior Data Platform Engineer to join our community!
We are a fast-growing startup in the software-as-a-service and AI Security Industry. We provide innovative solutions to securing the whole organization-to-SaaS surface. (More details: https://grip.security)
Using the newest technologies, we're working on solving a huge problem all enterprises face today - to govern the accessibility of all their employees to all 3rd party vendors (GitHub, SendGrid, Atlassian, and thousands more!), and ensure there is no leftover/unwanted access to any of the organization's SaaS and AI assets. The SaaS and AI security field is complex and challenging; therefore, we're looking for super-talented people, who are not afraid of technical challenges and breaking down barriers to achieve good solutions.
The job
As a Senior Data Platform Engineer, you will play a key role in building and evolving Grips modern data platform - the infrastructure that powers product features and analytics across the company.
You will focus on designing and operating scalable, reliable data systems and platform tooling that support our Data Lakehouse, enabling engineers, analysts and research teams to work with data efficiently and with minimal friction.
Responsibilities:
Design, build and operate a cloud-native modern data platform.
Develop and optimize data processing frameworks and pipelines across batch and streaming workloads.
Improve developer experience and platform usability through tooling and automation.
Lead and support large-scale data migrations and architectural improvements.
Drive best practices around infrastructure, CI/CD, testing, and system design.
Collaborate with developers, analysts, data scientists and other stakeholders to develop new products and features.
Contribute to a strong engineering culture of ownership, learning, and knowledge sharing.
Requirements:
5+ years of hands-on experience building scalable data infrastructure, particularly around data lake or data warehouse architectures.
Proven experience designing, building and operating production-grade systems and services.
Strong understanding of cloud infrastructure (AWS, GCP, or Azure) and hands-on experience with modern data platforms and tools (e.g., Spark, Kafka, Airflow, dbt, open table formats, or similar).
Strong programming skills in Python and SQL.
Independent, proactive, and ownership-driven mindset.
Background in data platform engineering, backend engineering, DevOps, or DBA - strong advantage.
Experience with containerization technologies - advantage.
This position is open to all candidates.
 
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Senior Backend Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power our Health.

Youll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.

How will you contribute?
Design, implement, and maintain scalable and reliable data pipelines and backend systems supporting both operational and analytical needs, with a focus on ML/AI product enablement.
Ensure data processing is optimized for speed, efficiency, and fault tolerance, enabling seamless integration with AI/ML workflows and reliable performance across all our Health products.
Monitor and improve uptime, reliability, and observability of our data infrastructure and pipelines.
Build and maintain systems to ensure data quality, consistency, and usability across the organization, enabling advanced analytics and AI solutions.
Work closely with product and engineering teams to deliver new features rapidly and with a high standard of technical excellence.
Drive innovation in how we build, measure, and optimize data features, backend services, and AI product integrations.
Participate in on-call rotations with a service-oriented approach and fast responsiveness.
Lead scalability efforts to support increasing data volumes, expanding AI/ML initiatives, and new product launches.
דרישות:
Who are you?
You are a seasoned backend or data engineer with experience working on production-grade ML/AI-powered products. You thrive in fast-paced, high-ownership environments and are passionate about building scalable and reliable systems. You understand the unique requirements of delivering AI/ML features in production, and you are comfortable working with modern technologies in the LLM/RAG ecosystem.
You pride yourself on delivering high-quality solutions quickly, without sacrificing design or reliability. Youre known for your responsiveness, collaborative spirit, and service-oriented mindset-especially when youre on-call and the stakes are high.

At least 5 years of experience with Python in backend or data engineering roles, designing and operating large-scale data pipelines, backend services, and data infrastructure in production environments.
Hands-on experience working on ML/AI-powered products in production, with strong understanding of requirements for integrating data platforms with AI features.
Familiarity with modern LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) technologies, and experience supporting their deployment or integration.
Familiar with or have worked with these technologies (or alternatives):
Data Processing & Streaming: Apache Spark, DBT, Airflow, Airbyte, Kafka
API Development: FastAPI, micro-service architecture, SFTP
Data Storage: Data Lakehouse architectures, Apache Iceberg, Vector Databases, RDS
ML/AI: ML/LLM libraries and frameworks (such as Gemini, Hugging Face, etc.)
Cloud Infrastructure: AWS stack (S3, Firehose, Lambda, Athena, etc.), Kubernetes (K8s)
Demonstrated ability to optimize performance and ensure high availability, scalability, and reliability of backend/data systems.
Strong foundation in best practices for data quality, governance, security, and observability.
Ability to collaborate effectively with engineering, data science, and product teams in a cross-functional setting.
Track record of innovative thinkin המשרה מיועדת לנשים ולגברים כאחד.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a highly skilled Senior Data Engineer with strong architectural expertise to design and evolve our next-generation data platform. You will define the technical vision, build scalable and reliable data systems, and guide the long-term architecture that powers analytics, operational decision-making, and data-driven products across the organization.

This role is both strategic and hands-on. You will evaluate modern data technologies, define engineering best practices, and lead the implementation of robust, high-performance data solutions-including the design, build, and lifecycle management of data pipelines that support batch, streaming, and near-real-time workloads.

What Youll Do

Architecture & Strategy
Own the architecture of our data platform, ensuring scalability, performance, reliability, and security.
Define standards and best practices for data modeling, transformation, orchestration, governance, and lifecycle management.
Evaluate and integrate modern data technologies and frameworks that align with our long-term platform strategy.
Collaborate with engineering and product leadership to shape the technical roadmap.

Engineering & Delivery
Design, build, and manage scalable, resilient data pipelines for batch, streaming, and event-driven workloads.
Develop clean, high-quality data models and schemas to support analytics, BI, operational systems, and ML workflows.
Implement data quality, lineage, observability, and automated testing frameworks.
Build ingestion patterns for APIs, event streams, files, and third-party data sources.
Optimize compute, storage, and transformation layers for performance and cost efficiency.

Leadership & Collaboration
Serve as a senior technical leader and mentor within the data engineering team.
Lead architecture reviews, design discussions, and cross-team engineering initiatives.
Work closely with analysts, data scientists, software engineers, and product owners to define and deliver data solutions.
Communicate architectural decisions and trade-offs to technical and non-technical stakeholders.
Requirements:
What Were Looking For:
6-10+ years of experience in Data Engineering, with demonstrated architectural ownership.
Expert-level experience with Snowflake (mandatory), including performance optimization, data modeling, security, and ecosystem components.
Expert proficiency in SQL and strong Python skills for pipeline development and automation.
Experience with modern orchestration tools (Airflow, Dagster, Prefect, or equivalent).
Strong understanding of ELT/ETL patterns, distributed processing, and data lifecycle management.
Familiarity with streaming/event technologies (Kafka, Kinesis, Pub/Sub, etc.).
Experience implementing data quality, observability, and lineage solutions.
Solid understanding of cloud infrastructure (AWS, GCP, or Azure).
Strong background in DataOps practices: CI/CD, testing, version control, automation.
Proven leadership in driving architectural direction and mentoring engineering teams.

Nice to Have:
Experience with data governance or metadata management tools.
Hands-on experience with DBT, including modeling, testing, documentation, and advanced features.
Exposure to machine learning pipelines, feature stores, or MLOps.
Experience with Terraform, CloudFormation, or other IaC tools.
Background designing systems for high scale, security, or regulated environments.

Additional Skills:
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Release Management, Security-First Mindset, User Experience (UX).
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
5+ years as a Data Engineer with production-grade Python and SQL
Solid data warehousing experience (e.g., Snowflake, Databricks, Redshift, BigQuery).
Hands-on AWS familiarity: Lambda, S3, SNS/SQS, Firehose, and related lake/ingestion patterns.
Platform mindset: reliability, observability, and systematic production debugging.
Terraform/IaC skills: read, modify, and ship changes for EKS-based deployments.
AI tooling fluency: Cursor/Claude as a primary workflow, can navigate unfamiliar codebases with AI assistance
Experienced with modern data stack tooling; DBT, Airflow, and Iceberg storage are a significant advantage, as is familiarity with AWS big data services and BI tools such as Looker or Tableau
Passionate about data and genuinely curious about technology - you're the kind of person who identifies a gap, designs a solution, and sees it through without being asked
A strong collaborator who thrives working across engineering and business teams, comfortable translating ambiguous business needs into precise, well-designed data models
Self-driven and comfortable navigating complexity independently - you bring clarity to hard problems and raise the bar for the people around you.
This position is open to all candidates.
 
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17/05/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
We are looking for a Senior Analytics Engineer to help design and build the engineering foundation that powers analytics across the organization.
Our goal is to create a modern data environment where analytics development is fast, reliable, scalable, and increasingly automated. This includes building strong data warehouse foundations, scalable modeling layers, and introducing AI-powered tools and automation that accelerate how data products are built and used.
In this role, you will be part of an analytics squad, working closely with analysts and business stakeholders while building the infrastructure, automation frameworks, and intelligent tooling that enable analytics to scale across the organization.
This is a unique opportunity to help build the next generation of the data organization.
Key Responsibilities:
Lead AI adoption in the analytics platform, building tools and workflows that automate analytics development, dashboards, and data exploration
Design and build scalable data warehouse models and transformation layers
Build and optimize ETL pipelines and core analytics infrastructure (Bronze / Silver)
Improve performance, reliability, and scalability of the analytics platform
Develop automation and internal tools that accelerate analytics workflows
Enable self-serve data access across the company through semantic layers and reusable datasets
Collaborate with analysts and business teams within an analytics squad
Requirements:
6+ years of experience in Data Engineering and Analytics Engineering roles, building modern data warehouses and analytics platforms using technologies such as BigQuery, dbt, and Python
Experience with workflow orchestration (Dagster, Airflow, or equivalent) and building reliable, observable data pipelines
Hands-on experience using AI coding platforms and tools to automate data engineering and analytics workflows
Strong engineering practices including version control (Git), testing, code reviews, and CI/CD
Experience building automation systems and internal tools for data teams
Experience working closely with analysts, product teams, and business stakeholders in analytics-driven environments
Strong problem-solving skills with a builder mindset
This position is open to all candidates.
 
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לפני 4 שעות
חברה חסויה
Job Type: Full Time
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.
Requirements:
4+ years of experience as a Data Engineer.
4+ years of Python and SQL experience.
4+ years of direct experience with SQL (Redshift/Snowflake), data modeling, data warehousing, and building ELT/ETL pipelines (DBT & Airflow preferred).
3+ years of experience in scalable data architecture, fault-tolerant ETL, and data quality monitoring in the cloud.
Hands-on experience with cloud environments (AWS preferred) and big data technologies (EMR, EC2, S3, Snowflake, Spark Streaming, Kafka, DBT).
Strong troubleshooting and debugging skills in large-scale systems.
Deep understanding of distributed data processing and tools such as Kafka, Spark, and Airflow.
Experience with design patterns, coding best practices, and data modeling.
Proficiency with Git and modern source control.
Basic Linux/Unix system administration skills.
Experience with AI tools and a strong interest in continuously exploring and applying them in everyday work are highly valued.
Nice to Have:
Familiarity with fintech business processes (funding, securitization, loan servicing, accounting).- Huge advantage
BS/MS in Computer Science or related field.
Experience with NoSQL or large-scale DBs.
DevOps experience in AWS.
Microservices experience.
2+ years of experience in Spark and the broader Data Engineering ecosystem.
This position is open to all candidates.
 
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4 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Data Platform Team Lead to play a pivotal role in building and maintaining our robust data platform. You will lead a talented team of data engineers ensuring a collaborative and high-performing environment within and outside the team.

The ideal candidate must have excellent business understanding, attention to detail, technical and analytical abilities, and a deep Data Engineeiring understanding. The candidate will be self-driven, independent, able to coordinate with different teams and groups and handle ambiguity well within the organization.

How will you contribute?
Provide technical leadership and direction for the data platform, including data pipelines, data lake, data governance, and data security.
Partner with data analysts and BI analysts to understand their needs and ensure the platform effectively supports their work.
Design, develop, and implement solutions to optimize data ingestion, storage, processing, and analysis.
Oversee data platform projects
Build self-serve accessibility tools and platforms for the entire company to use
Foster a culture of collaboration and continuous improvement within the data teams.
Mentor and develop the technical and analytical skills of the team members.
Stay up-to-date on the latest trends and technologies in data platforms and analytics.
Communicate effectively with stakeholders across technical and non-technical departments.
Requirements:
Require Skills and Experience:
5+ years of experience in data engineering or a related field - must.
2+ years of proven experience in leading and managing a data team - must.
Fluency in Python, Airflow and DBT - must.
Proficiency in data modeling, ETL, SQL, data visualization and BI tools - must.
Strong technical skills in data platform technologies like Spark, Kafka, Athena, cloud platforms (AWS, Azure, GCP) and orchestration frameworks - must.
Ability to learn new technologies and lead complex projects.
Solid understanding of data lake concepts and data modeling principles.
Experience in global data and BI project management.
Excellent analytical and problem-solving skills.
Strong communication and collaboration skills - Hebrew and English - written and verbal.
Experience with data governance and data security best practices - advantage.


What qualifications and skills will help you to be successful?
Accountability - we can trust you to take ownership of your tasks from A-Z and understand the gravity of the data you are working with.
Agility and adaptability - we can trust you to get things done, learn what it takes on your own and adapt to a very dynamic environment
Communication - you are able to successfully communicate complex issues and problems
An analytical mind with problem-solving capabilities
Great interpersonal skills
This is a unique opportunity to join a startup that is having a meaningful impact on the well-being and mental health of thousands.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

We are looking for a talented Data Engineer to help build and enhance the data platform that supports analytics, operations, and data-driven decision-making across the organization. You will work hands-on to develop scalable data pipelines, improve data models, ensure data quality, and contribute to the continuous evolution of our modern data ecosystem.

Youll collaborate closely with Senior Engineers, Analysts, Data Scientists, and stakeholders across the business to deliver reliable, well-structured, and well-governed data solutions.


What Youll Do
Engineering & Delivery
Build, maintain, and optimize data pipelines for batch and streaming workloads.

Develop reliable data models and transformations to support analytics, reporting, and operational use cases.

Integrate new data sources, APIs, and event streams into the platform.

Implement data quality checks, testing, documentation, and monitoring.

Write clean, performant SQL and Python code.

Contribute to improving performance, scalability, and cost-efficiency across the data platform.

Collaboration & Teamwork

Work closely with senior engineers to implement architectural patterns and best practices.

Collaborate with analysts and data scientists to translate requirements into technical solutions.

Participate in code reviews, design discussions, and continuous improvement initiatives.

Help maintain clear documentation of data flows, models, and processes.

Platform & Process

Support the adoption and roll-out of new data tools, standards, and workflows.

Contribute to DataOps processes such as CI/CD, testing, and automation.

Assist in monitoring pipeline health and resolving data-related issues.
Requirements:
What Were Looking For:

2-5+ years of experience as a Data Engineer or similar role.

Hands-on experience with Snowflake (mandatory)-including SQL, modeling, and basic optimization.

Experience with dbt (or similar)-model development, tests, documentation, and version control workflows.

Strong SQL skills for data modeling and analysis.

Proficiency with Python for pipeline development and automation.

Experience working with orchestration tools (Airflow, Dagster, Prefect, or equivalent).

Understanding of ETL/ELT design patterns, data lifecycle, and data modeling best practices.

Familiarity with cloud environments (AWS, GCP, or Azure).

Knowledge of data quality, observability, or monitoring concepts.

Good communication skills and the ability to collaborate with cross-functional teams.


Nice to Have:

Exposure to streaming/event technologies (Kafka, Kinesis, Pub/Sub).

Experience with data governance or cataloging tools.

Basic understanding of ML workflows or MLOps concepts.

Experience with infrastructure-as-code tools (Terraform, CloudFormation).

Familiarity with testing frameworks or data validation tools.

Additional Skills:
Cloud Architectures, Cross Domain Knowledge, Design Thinking, Development Fundamentals, DevOps, Distributed Computing, Microservices Fluency, Full Stack Development, Security-First Mindset, User Experience (UX)
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
Qualifications & Skills:

Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.

Minimum of 6 years of experience as a Data Engineer or a similar role, with a consistent record of successfully delivering ML/Data solutions.

You have built production data pipelines in the cloud, setting up data-lake and server-less solutions; ‌ you have hands-on experience with schema design and data modeling and working with ML scientists and ML engineers to provide production level ML solutions.

You have experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc)

Strong programming skills in languages such as Python and Java.

Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

Experience with Data Warehousing and ETL/ELT pipelines

Experience in data processing for large-scale language models like GPT, BERT, or similar architectures - an advantage.

Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.

Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.

Experience of working on products that impact a large customer base - an advantage.

Excellent communication in English; written and spoken.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8690216
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תיאור
שליחה
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v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
18/05/2026
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Software Engineer - Data Operations Platform to join our Data Operations team and help build the internal systems and platforms that power our data workflows at scale.

This is a unique opportunity for an early-career engineer who enjoys solving practical problems, building impactful tools, and working closely with data, AI, and operations teams. In this role, youll design and develop scalable internal platforms, automation systems, and AI-driven workflows that support large-scale data operations, including tooling for computer vision workflows, automated QA systems, taxonomy management, and database navigation tools used daily across the company.

As part of a fast-moving startup and an industry leader in AI-driven creative analytics, your work will have a direct impact on engineering efficiency, workflow automation, system scalability, and data quality.



Key Responsibilities

Design, develop, and maintain internal tools and systems that support Data Operations workflows.
Build scalable automation systems for QA processes, taxonomy applications, and large-scale data handling.
Collaborate closely with Data, AI, Product, and Operations teams to solve practical business and operational challenges.
Write clean, maintainable, and reliable code with a strong focus on usability, scalability, and efficiency.
Improve internal workflows by identifying bottlenecks and building scalable solutions.
Work with databases and data pipelines to support operational and analytical needs.
Troubleshoot issues, optimize existing tools, and continuously improve system reliability and performance.
Contribute ideas, experiment with new technologies, and help improve developer workflows and internal processes.
Requirements:
1-2 years of software engineering experience.
Strong programming fundamentals and problem-solving skills.
Comfort working with data-intensive systems and operational workflows.
Experience with Python, automation scripting, SQL, and relational databases.
Exposure to AI tools, computer vision, machine learning workflows, or data pipelines - a plus.
Experience building internal tools, platforms, or automation systems - a plus.
Pragmatic, proactive, and adaptable mindset with a strong sense of ownership and execution.
Curiosity about data operations, AI workflows, and internal tooling in a fast-paced startup environment.
Strong written and verbal communication skills in English.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8656407
סגור
שירות זה פתוח ללקוחות VIP בלבד
סגור
דיווח על תוכן לא הולם או מפלה
מה השם שלך?
תיאור
שליחה
סגור
v נשלח
תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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.
Requirements:
Qualifications & Skills:

Bachelors or masters degree in computer science, Engineering, Statistics, or a related field.

Minimum of 3 years of experience as a Data Engineer or a similar role, with a consistent record of successfully delivering ML/Data solutions.

You have built production data pipelines in the cloud, setting up data-lake and server-less solutions; ‌ you have hands-on experience with schema design and data modeling and working with ML scientists and ML engineers to provide production level ML solutions.

You have experience designing systems E2E and knowledge of basic concepts (lb, db, caching, NoSQL, etc)

Strong programming skills in languages such as Python and Java.

Experience with big data processing frameworks such, Pyspark, Apache Flink, Snowflake or similar frameworks.

Demonstrable experience with MySQL, Cassandra, DynamoDB or similar relational/NoSQL database systems.

Experience with Data Warehousing and ETL/ELT pipelines

Experience in data processing for large-scale language models like GPT, BERT, or similar architectures - an advantage.

Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib - an advantage.

Experience with experimental design, A/B testing, and evaluation metrics for ML models - an advantage.

Experience of working on products that impact a large customer base - an advantage.

Excellent communication in English; written and spoken.
This position is open to all candidates.
 
Show more...
הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8690239
סגור
שירות זה פתוח ללקוחות VIP בלבד