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6 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We're looking for a Data Engineer to own and evolve the data infrastructure that sits underneath all of it. The pipeline is already built and running at real scale. Your job is to go deeper - embedding data further into the business and pushing the AI/ML layer forward. This isn't a maintenance role. It's an ownership role.

In this role, you will:

Our data pipelines run faster, scale cleaner, and break less - because you own the architecture and optimization of our BigQuery warehouse end-to-end.
High-throughput processing and real-time analytics become possible at a scale we haven't reached yet - because you're shaping the distributed systems that get us there.
Data capabilities land in the hands of the people who need them - data scientists, engineers, and product stakeholders from problem to solution, not as a downstream dependency.
The infrastructure gets more reliable, more automated, and easier to monitor - because you treat DevOps and MLOps as part of the job, not someone else's problem.
AI/ML models move from development into production and stay there - not handed off, but owned through the full deployment lifecycle.
Requirements:
Must have:

4+ years building high-scale data pipelines and managing cloud data warehouses (BigQuery strongly preferred)
Hands-on experience with Kafka, CDC tools (Estuary or similar), and pipeline orchestration (Airflow, dbt)
Deep command of SQL and NoSQL ecosystems - Postgres, Redis, Elastic
Solid backend development skills with strong OOP/OOD fundamentals
Exposure to MLOps and production AI/ML model deployment
Experience with AI-assisted development tools (Claude Code, GitHub Copilot, Cursor)
Comfortable working independently with minimal structure - you drive things, you don't wait for them
Good to have:

Familiarity with DevOps and async systems: Pulumi/Terraform, RabbitMQ, Docker, WebSockets, Linux
Experience with routing and navigation algorithms
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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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
We are looking for a Senior Data Engineer to take ownership of our evolving data platform.
Our data environment is entering a significant growth phase. We are strengthening our Redshift-based warehouse, expanding our transformation capabilities with dbt, and investing in modern engineering standards across the stack.
In parallel, we are building a dedicated application layer for delivering data products. This role is responsible for designing and owning the data foundations that support it.
AI-assisted development is not a side experiment. It is a core part of how we engineer. We expect this role to actively leverage advanced AI development tools as part of daily work, accelerating design, implementation, validation and documentation while maintaining strong architectural judgment and production-level quality.
This position requires architectural thinking, long-term platform vision and the ability to lead complex initiatives from design through production in an AI-augmented engineering environment.
What You Will Do:
Own the architecture and evolution of our cloud-based Data Warehouse.
Lead complex data initiatives end to end, from requirements definition and technical design through implementation, deployment and post-production optimization.
Apply AI-assisted development workflows to improve engineering velocity, code quality and system reliability.
Design and evolve transformation standards and modeling practices using dbt as a strategic layer within the team.
Architect the data foundations that power our data-driven applications.
Translate business needs into structured, production-grade data solutions.
Drive technical standards, consistency and engineering discipline across the data stack.
Take full accountability for delivery, stability and long-term scalability of the systems you build.
Requirements:
8+ years of experience in Data Engineering with strong focus on modern cloud-based DWH architecture.
Proven experience leading projects end to end in production data environments.
Deep production experience with Redshift, dbt and orchestration frameworks such as Airflow.
Strong SQL expertise and solid understanding of dimensional modeling and transformation best practices.
Practical, daily experience using AI development tools as part of your engineering workflow.
Ability to critically evaluate AI-generated output and maintain high architectural and production standards.
Strong system design capabilities and full ownership mindset.
Experience supporting data products or application-facing data environments.
Ability to balance speed with quality and long-term architectural thinking.
This position is open to all candidates.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Lead the team building the agentic infrastructure powering Klaudia - our AI SRE. You'll own the architecture, set the technical direction, and push experimental ideas into production.

This isn't a coordination role. You'll be a technical leader who builds alongside your team - setting the bar for architecture quality, driving experimental bets, and turning research into production-grade systems.



What will you do?

Own the agentic infrastructure- You're responsible for the architecture of Klaudia's core - the systems that make autonomous investigation, root cause analysis, and self-healing possible at scale.

Build and grow your team- Hire great engineers, mentor them, run meaningful design reviews, and build a culture of high ownership and engineering excellence.

Drive experimental development- Run structured bets - LLM evaluation frameworks, new agent architectures, novel tool-use patterns - and bring the best ones to production.

Stay hands-on You'll design systems, review PRs critically, and write code where it matters. Your technical credibility is the foundation of your leadership.

Shape our AI strategy- Work closely with product and R&D leadership to define what Klaudia becomes next.



Why this role rocks?

Category-defining work- AI SRE is the hottest space in cloud infra. You'll be leading the team that defines what it means - not catching up to anyone.

Real autonomy- You'll set the technical roadmap for Core. No pre-solved problems handed down to you - you decide what gets built and how.

Build something that lasts- Hire and shape a team from an early stage. Your engineering culture decisions here will compound for years.

Serious engineering culture- High bar for craft, strong team around you, and leadership that respects technical depth over process theater.
Requirements:
Proven tech leader- 8+ years of backend engineering experience, including at least 2 years in a tech lead or team lead capacity. You've owned systems end-to-end, not just delivered tickets.

Proven ability to build teams- You've hired engineers you're proud of, mentored people to grow beyond where they thought they could, and created an environment where ownership is the default.

Deep experience with distributed systems- Concurrency, reliability, observability - you design for failure, not around it.

Experience building with AI-assisted tools- (e.g Cursor, Claude Code, etc.) You treat these as serious multipliers, not toys.

Strong communicator- You can hold a design review, align with product leadership, and explain a tricky architecture decision to an engineer in their first week - all with the same clarity.

Comfortable with open-ended problems- You enjoy tackling challenges that don't have a simple one-prompt AI answer - where the path forward requires judgment, not just execution.
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
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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.
 
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חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
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
Requirements:
7+ years as a BI Engineer or Data Engineer, with 2+ in a technical leadership or architect role
Proven experience managing complex data warehouses that serve multiple products and entire organizations
Strong expertise in data modeling, ELT development, and data warehouse methodologies
Advanced SQL skills and hands-on experience with Snowflake or similar cloud-native data warehouse platforms
Extensive experience with dbt for data transformation and modeling
Python and software development experience (a strong plus)
Excellent communication skills - you can mentor technical team members and explain complex data concepts to business stakeholders
Ready to work in an office environment most days of the week
Enthusiasm about learning and adapting to the exciting world of AI - a commitment to exploring this field is a fundamental part of our culture
This position is open to all candidates.
 
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Location: Tel Aviv-Yafo
Job Type: Full Time and Hybrid work
we are growing fast, and as we grow we scale both in the number of patients we treat and in the number of products we have in our portfolio. Your mission is to design and build the next-generation data infrastructure and pipelines, in addition contributing to an ongoing project that serves both our customers and internal data teams with scalable and reliable solutions.

You will:
Make a critical contribution to shaping and developing the core of our Data Platform used for AI research and business intelligence, from design to implementation.

Design and build complex data pipelines to move and manipulate data from a wide variety of data sources.

Create a system that will be used to support our data product offering.

Closely collaborate with various teams, including Software Engineering, AI Engineering and Product Management .
Tech stack:

We are running on AWS with Python as the main programming language for the backend. We are using various technologies such as S3, DBT, ETL, ELT, Spark, DynamoDB, Postgres, RabbitMQ, Docker, Redis, Prometheus, Terraform and others. We are always open to new technologies and tools that will help us to do our job even better.

What success looks like:
Self-contributor who excels at working independently and can also collaborate effectively as a valuable team member.

Mentor and advise other team members in code review, performance, scalability and more.

Eager to learn new things and also proactively suggest new ideas and initiatives.

Excellent communication and collaboration skills.

Team player, highly motivated, can-do approach.
Requirements:
A team player with a strong can do mentality.

6+ years of professional experience as a data engineer.

5+ years of experience with Python or similar programming languages.

Proven experience in data pipeline architecture, including working on ETL, ELT projects in a production environment.

Experience with SQL, NonSQL databases, and data lakes.

Experience working with AI and LLM tools such as Cursor, Claude Code or similar.

Experience working with terraform, CDC, DBT, Github or IaC in general

Experience working with AWS in a production cloud environment and AWS services such as Glue, Athena.

Excellent design capabilities: understanding complex requirements, architectural considerations, and having the proven ability to design flexible, reliable, and scalable solutions.

Experience with micro services architecture and distributed systems -
Advantage

B.Sc. or higher in Computer Science or in a similar field.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8656404
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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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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8654131
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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 :)
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. As the Groups Tech Lead, youll shape and implement the technical vision and architecture while staying hands-on across three specialized teams: Data Engineering Infra, Machine Learning Platform, and Data Warehouse Engineering, forming the backbone of data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives toward becoming the most precise and efficient insurance company on the planet. By embracing Data Mesh principles, we create tools that empower teams to own their data while leveraging a robust, self-serve data infrastructure. This approach enables Data Scientists, Analysts, Backend Engineers, and other stakeholders to seamlessly access, analyze, and innovate with reliable, well-modeled, and queryable data, at scale.
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 youll :
Technically lead the group by shaping the architecture, guiding design decisions, and ensuring the technical excellence of the Data Platforms three teams
Design and implement data solutions that address both applicative needs and data analysis requirements, creating scalable and efficient access to actionable insights
Drive initiatives in Data Engineering Infra, including building robust ingestion layers, managing streaming ETLs, and guaranteeing data quality, compliance, and platform performance
Develop and maintain the Data Warehouse, integrating data from various sources for optimized querying, analysis, and persistence, supporting informed decision-makingLeverage data modeling and transformations to structure, cleanse, and integrate data, enabling efficient retrieval and strategic insights
Build and enhance the Machine Learning Platform, delivering infrastructure and tools that streamline the work of Data Scientists, enabling them to focus on developing models while benefiting from automation for production deployment, maintenance, and improvements. Support cutting-edge use cases like feature stores, real-time models, point-in-time (PIT) data retrieval, and telematics-based solutions
Collaborate closely with other Staff Engineers across to align on cross-organizational initiatives and technical strategies
Work seamlessly with Data Engineers, Data Scientists, Analysts, Backend Engineers, and Product Managers to deliver impactful solutions
Share knowledge, mentor team members, and champion engineering standards and technical excellence across the organization
דרישות:
8+ years of experience in data-related roles such as Data Engineer, Data Infrastructure Engineer, BI Engineer, or Machine Learning Platform Engineer, with significant experience in at least two of these areas
A B.Sc. in Computer Science or a related technical field (or equivalent experience)
Extensive expertise in designing and implementing Data Lakes and Data Warehouses, including strong skills in data modeling and building scalable storage solutions
Proven experience in building large-scale data infrastructures, including both batch processing and streaming pipelines
A deep understanding of Machine Learning infrastructure, including tools and frameworks that enable Data Scientists to efficiently develop, deploy, and maintain models in production, an advantage
Proficiency in Python, Pulumi/Terraform, Apache Spark, AWS, Kubernetes (K8s), and Kafka for building scalable, reliable, and high-performing data solutions
Strong knowledge of databases, including SQL (schema design, query optimization) and NoS המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8644051
סגור
שירות זה פתוח ללקוחות VIP בלבד