Data Engineer -GCP & BigQuery Expert

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לפני 1 שעות

Data Engineer

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 an 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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לפני 1 שעות

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

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.

This position is open to all candidates.

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לפני 19 שעות

ML Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time and Hybrid work

Required ML Data Engineer
Israel: Tel Aviv/ Hybrid (Israel)
R&D | Full Time | Job Id: 24792
Key Responsibilities
Your Impact & Responsibilities:
As a Data Engineer - AI Technologies, you will be responsible for building and operating the data foundation that enables our LLM and ML research: from ingestion and augmentation, through labeling and quality control, to efficient data delivery for training and evaluation.
You will:
Own data pipelines for LLM training and evaluation
Design, build and maintain scalable pipelines to ingest, transform and serve large-scale text, log, code and semi-structured data from multiple products and internal systems.
Drive data augmentation and synthetic data generation
Implement and operate pipelines for data augmentation (e.g., prompt-based generation, paraphrasing, negative sampling, multi-positive pairs) in close collaboration with ML Research Engineers.
Build tagging, labeling and annotation workflows
Support human-in-the-loop labeling, active learning loops and semi-automated tagging. Work with domain experts to implement tools, schemas and processes for consistent, high-quality annotations.
Ensure data quality, observability and governance
Define and monitor data quality checks (coverage, drift, anomalies, duplicates, PII), manage dataset versions, and maintain clear documentation and lineage for training and evaluation datasets.
Optimize training data flows for efficiency and cost
Design storage layouts and access patterns that reduce training time and cost (e.g., sharding, caching, streaming). Work with ML engineers to make sure the right data arrives at the right place, in the right format.
Build and maintain data infrastructure for LLM workloads
Work with cloud and platform teams to develop robust, production-grade infrastructure: data lakes / warehouses, feature stores, vector stores, and high-throughput data services used by training jobs and offline evaluation.
Collaborate closely with ML Research Engineers and security experts
Translate modeling and security requirements into concrete data tasks: dataset design, splits, sampling strategies, and evaluation data construction for specific security use.

Requirements:
3+ years of hands-on experience as a Data Engineer or ML/Data Engineer, ideally in a product or platform team.
Strong programming skills in Python and experience with at least one additional language commonly used for data / backend (e.g., SQL, Scala, or Java).
Solid experience building ETL / ELT pipelines and batch/stream processing using tools such as Spark, Beam, Flink, Kafka, Airflow, Argo, or similar.
Experience working with cloud data platforms (e.g., AWS, GCP, Azure) and modern data storage technologies (object stores, data warehouses, data lakes).
Good understanding of data modeling, schema design, partitioning strategies and performance optimization for large datasets.
Familiarity with ML / LLM workflows: train/validation/test splits, dataset versioning, and the basics of model training and evaluation (you dont need to be the primary model researcher, but you understand what the models need from the data).
Strong software engineering practices: version control, code review, testing, CI/CD, and documentation.

Ability to work independently and in collaboration with ML engineers, researchers and security experts, and to translate high-level requirements into concrete data engineering tasks.
Nice to Have
Experience supporting LLM or NLP workloads, including dataset construction for pre-training / fine-tuning, or retrieval-augmented generation (RAG) pipelines.
Familiarity with ML tooling such as experiment tracking (e.g., Weights & Biases, MLflow) and ML-focused data tooling (feature stores, vector databases).
Background in security / cyber domains (logs, alerts, incidents, SOC workflows) or other high-volume, high-variance data environments.

This position is open to all candidates.

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2 ימים

Data Group Tech Lead, Staff Engineer

חברה חסויה

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. 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 our data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives us 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 NoSQ המשרה מיועדת לנשים ולגברים כאחד.

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8594845

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22/02/2026

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

we are looking for a Senior Data Engineer.
As a Senior Data Engineer, you will play a key role in shaping and driving our analytics data pipelines and solutions to empower business insights and decisions. Collaborating with a variety of stakeholders, you will design, develop, and optimize scalable, high-performance data analytics infrastructures using modern tools and technologies. Your work will ensure data is accurate, timely, and actionable for critical decision-making.
Key Responsibilities:
Lead the design, development, and maintenance of robust data pipelines and ETL processes, handling diverse structured and unstructured data sources.
Collaborate with data analysts, data scientists, product engineers and product managers to deliver impactful data solutions.
Architect and maintain the infrastructure for ingesting, processing, and managing data in the analytics data warehouse.
Develop and optimize analytics-oriented data models to support business decision-making.
Champion data quality, consistency, and governance across the analytics layer.

Requirements:
5+ years of experience as a Data Engineer or in a similar role.
Expertise in SQL and proficiency in Python for data engineering tasks.
Proven experience designing and implementing analytics-focused data models and warehouses.
Hands-on experience with data pipelines and ETL/ELT frameworks (e.g Airflow, Luigi, AWS Glue, DBT).
Strong experience with cloud data services (e.g., AWS, GCP, Azure).
A deep passion for data and a strong analytical mindset with attention to detail.
Bonus points:
Strong understanding of business metrics and how to translate data into actionable insights
Experience with data visualization tools (e.g., Tableau, Power BI, Looker)
Familiarity with data governance and data quality best practices
Excellent communication skills to work with cross-functional teams including data analysts, data scientists, and product managers

This position is open to all candidates.

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05/03/2026

Senior Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

Join global data team building the infrastructure that powers analytics and AI-driven insights across the organization. As a Data Engineer, you'll design and maintain scalable data pipelines and systems that enable product analytics, business intelligence, and AI applications in our high-growth fintech environment.
What you'll do:
Design, build, and maintain robust batch and streaming pipelines and orchestration across our modern stack (AWS, DBT, Airbyte, Airflow, Snowflake) to support AI-driven data products.
Develop and optimize data models in Snowflake, ensuring data quality, consistency, and performance at scale.
Collaborate with Product Analysts and AI specialists to implement data solutions for customer segmentation, ranking systems, and predictive models.
Partner with cros-functional teams to translate technical requirements into scalable data architecture.
Implement end-to-end observability (data quality checks, monitoring, alerting) and cost/performance optimization in Snowflake and AWS.

Requirements:
6+ years of experience as a Data Engineer or similar role.
Expert proficiency in SQL and hands-on experience with modern data warehouse platforms (Snowflake - advantage).
Strong experience building ETL/ELT pipelines using tools like DBT, Airflow, or similar orchestration frameworks.
Proficiency in Python or another programming language for data processing.
Solid understanding of data modeling techniques (dimensional modeling, Data Vault, etc).
Experience with cloud platforms, preferably AWS.
Proven ability to design and maintain reliable, scalable data systems with a strong focus on data quality.
Strong communication skills and the ability to work effectively with both technical and business stakeholders.
Experience with fintech, financial services, or cryptocurrency/blockchain - advantage.
Familiarity with real-time data processing or streaming technologies - advantage.

This position is open to all candidates.

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לפני 20 שעות

Data Platform Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time and Hybrid work

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

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

What you'll do:

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

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

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

Create and maintain documentation for data platforms and processes.

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

Troubleshoot and resolve data infrastructure issues efficiently.

Monitor system performance and implement optimizations.

Stay current with emerging technologies and implement innovative solutions.

Requirements:
What you'll bring:

3+ years experience in data engineering or platform engineering roles.

Strong programming skills in Python and SQL.

Experience with orchestration platforms like Airflow/Dagster/Temporal.

Experience with MPPs like Snowflake/Redshift/Databricks.

Hands-on experience with cloud platforms (AWS) and their data services.

Understanding of data modeling, data warehousing, and data lake concepts.

Ability to optimize data infrastructure for performance and reliability.

Experience working with containerization (Docker) in Kubernetes environments.

Familiarity with CI/CD concepts.

Fluent in English, both written and verbal.

And it would be great if you have (optional):

Experience with big data processing frameworks (Apache Spark, Hadoop).

Experience with stream processing technologies (Flink, Kafka, Kinesis).

Knowledge of infrastructure as code (Terraform).

Experience building analytics platforms.

Experience building clickstream pipelines.

Familiarity with machine learning workflows and MLOps.

Experience working in a startup environment or fintech industry.

This position is open to all candidates.

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26/02/2026

Marketing Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

We are looking for an Experienced Data Engineer to join our marketing team and take end-to-end ownership of our data platform and production data pipelines. In this role, you will be responsible for building robust, scalable, and observable data systems that power analytics, reporting, and downstream business use cases. You will work deeply hands-on with data infrastructure, modeling, and orchestration, and act as a key technical partner to Marketing, Sales Product and Business and Finance teams.
This role suits someone who enjoys working close to the metal, designing systems that scale, and solving ambiguous data problems in a dynamic startup environment. You will play a critical role in shaping how data flows through the company, setting engineering standards, and ensuring data is trustworthy, performant, and ready for growth.
What You'll Do:
Design, build, and maintain scalable, reliable data pipelines and data warehouse architectures to support analytics and business intelligence needs.
Own the end-to-end ETL/ELT processes - ingesting data from internal and external sources, transforming it, and making it analytics-ready.
Model and optimize data structures (fact tables, dimensions, semantic layers) to support performant querying and reporting.
Ensure high standards of data quality, integrity, observability, and reliability across all data assets.
Partner closely with Analytics, Product, Marketing, and Finance teams to understand data requirements and deliver robust data solutions.
Implement monitoring, alerting, and testing frameworks to proactively identify data issues.
Optimize warehouse performance and cost efficiency (query optimization, partitioning, clustering, etc.).
Identify gaps in data collection and work with engineering teams to improve instrumentation and data availability.
Support experimentation and analytics use cases by enabling clean, trustworthy datasets for A/B testing and analysis.
Document data models, pipelines, and best practices to support scale and knowledge sharing.

Requirements:
Bachelors or Masters degree in Computer Science, Data Engineering, Software Engineering, or a related technical field.
3-5 years of hands-on experience as a Data Engineer, preferably in a SaaS or technology-driven environment.
Strong experience designing and maintaining data warehouses (e.g., Snowflake, BigQuery, Redshift).
Proven expertise with ETL/ELT tools and frameworks (e.g., Airflow, dbt, Talend, SSIS, Informatica, or similar).
Advanced SQL skills and solid proficiency in Python (or similar languages) for data processing and orchestration.
Strong understanding of data modeling, warehousing best practices, and analytics engineering concepts.
Experience integrating data from business systems such as Salesforce, HubSpot, or other SaaS platforms.
Familiarity with SaaS metrics and business concepts (ARR, churn, LTV, CAC) - from a data modeling perspective.
Experience supporting BI tools and analytics consumers (Tableau, Looker, Power BI, etc.).
Strong problem-solving skills, attention to detail, and a passion for building reliable data foundations.
Excellent communication skills and the ability to collaborate across technical and non-technical teams.

This position is open to all candidates.

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לפני 23 שעות

Data Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time and Hybrid work

We are looking for a talented Data Engineer to join our analytics team in the Big Data Platform group.
Job Id: 25380
You will support our product and business data initiatives, expand our data warehouse, and optimize our data pipeline architecture with an AI first attitude.
The ideal candidate is experienced in leveraging AI tools as part of modern data pipeline development, enabling scalable solutions, accelerating delivery, and continuously exploring new approaches and technologies.
The right candidate is excited by the prospect of building the data architecture for the next generation of products and data initiatives.
This is a unique opportunity to join a team full of outstanding people making a big impact on us.
We work on multiple products in many domains to deliver truly innovative solutions in the Cyber Security and Big Data realm.
This role requires the ability to collaborate closely with both R&D teams and business stakeholders, to understand their needs and translate them into robust and scalable data solutions.
Key Responsibilities
Maintain and develop enterprise-grade Data Warehouse and Data Lake environments
Create data infrastructure for various R&D groups across the organization to support product development and optimization
Work with data experts to assist with technical data-related issues and support infrastructure needs
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, redesigning infrastructure for scalability
Build and maintain robust ETL/ELT pipelines for data ingestion, transformation, and delivery across various systems
Incorporate AI-assisted tools into data pipeline design, development, and optimization to improve efficiency, scalability, and innovation

Requirements:
B.Sc. in Engineering or a related field
3+ years of experience as a Data Engineer working on production systems
Advanced SQL knowledge and experience with relational databases
Proven experience using Python
Hands-on experience building, optimizing, and automating data pipelines, architectures, and data sets
Experience in creating and maintaining ETL/ELT processes
Strong project management and organizational skills
Strong collaboration skills with both technical (R&D) and non-technical (business) teams
Experience using AI tools as part of the data engineering workflow, with a mindset of experimentation, working at scale, and exploring new technologies
Advantage: Azure data services, Databricks, EventHub, and Spark.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8597003

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5 ימים

Data Infrastructure Engineer

חברה חסויה

Location: Tel Aviv-Yafo

Job Type: Full Time

As part of our Data Engineering team, you will not only build scalable data platforms but also directly enable portfolio growth by supporting new funding capabilities, loan sales and securitization, and improving cost efficiency through automated and trusted data flows that evolve our accounting processes.

Responsibilities

Design and build data solutions that support Sunbits 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.

This position is open to all candidates.

עדכון קורות החיים לפני שליחה

8591963

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