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27/01/2026
Location: Merkaz
Job Type: Full Time
abra professional services is seeking for an senior data engineer. We are seeking a Senior Data Engineer to lead the technical development of our Data Fabric within a military program. This role involves technical leadership in building contextual data pipelines, working with big data lakehouse architectures, and driving data pipeline automation.
Requirements:
MUST HAVE Requirements: 5+ years of hands-on experience as a Big Data Engineer
* Proven ability to design and deploy Big Data & AI solutions using frameworks and tools such as:
* Apache NiFi
* Kafka
* Spark
* Graph DB
* NoSQL databases Strong coding proficiency in Python and Bash
* Experience building large-scale data pipelines for data processing, transformation, and analytics
* Ability to define and manage metadata schemas
* Experience developing data workflows (e.g., metadata generation, auto-extraction, validation, format conversion)
* Experience developing tools for data observability and compliance analytics
* Ability to analyze and report on complex datasets and results
* Experience working with big data lakehouse architectures
* Ability to explore, enhance, and manage data fusion from multiple data sources
* Experience developing analytics tools, algorithms, and programs
* Technical leadership of data structure design for contextual pipelines
* Collaboration experience with Data Scientists and Architects
* Strong ability to work independently, learn new technologies, and apply innovative solutions
* Excellent interpersonal skills and ability to work as part of a team MSc in Computer Science or Data Science Advantages:
* Experience with managing metadata and taxonomy concepts alongside big data objects
* Experience working with public cloud Big Data & AI services
* Familiarity with machine learning concepts
* Strong technical skills
* Independent, hands-on developer
* Curious, open-minded, fast learner, and a strong team player
This position is open to all candidates.
 
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חברה חסויה
Location: Ra'anana
Job Type: Full Time
The ideal candidate is not afraid of data in any form or scale, and is experienced with cloud services to ingest, stream, store, and manipulate data. The Data Engineer will support new system designs and migrate existing ones, working closely with solutions architects, project managers, and data scientists. The candidate must be self-directed, a fast learner, and comfortable supporting the data needs of multiple teams, systems, and products. The right candidate will be excited by the prospect of optimizing or re-designing our customers data architecture to support their next generation of products, data initiatives, and machine learning systems.

Summary of Key Responsibilities:
To meet compliance and regulatory requirements, keep our customers data separated and secure.
Design, Build, and operate the infrastructure required for optimal data extraction, transformation, and loading from a wide variety of data sources using SQL, cloud migration tools, and big data technologies.
Optimize various RDBMS engines in the cloud and solve customers' security, performance, and operational problems.
Design, build, and operate large, complex data lakes that meet functional / non-functional business requirements.
Optimize various data types' ingestion, storage, processing, and retrieval, from near real-time events and IoT to unstructured data such as images, audio, video, documents, and in between.
Work with customers' and internal stakeholders including the Executive, Product, Data, Software Development and Design teams to assist with data-related technical issues and support their data infrastructure and business needs.
Requirements:
5+ years of experience in a Data Engineer role in a cloud native ecosystem.
3+ years of experience in AWS Data Services (mandatory).
Bachelor's (Graduate preferred) degree in Computer Science, Mathematics, Informatics, Information Systems or another quantitative field.
Working experience with the following technologies/tools:
big data tools: Spark, ElasticSearch, Kafka, Kinesis etc.
Relational SQL and NoSQL databases, such as MySQL or Postgres and DynamoDB or Cassandra.
Functional and scripting languages: Python, Java, Scala, etc.
Advanced SQL.
Experience building and optimizing big data pipelines, architectures and data sets.
Working knowledge of message queuing, stream processing, and highly scalable big data stores.
Experience supporting and working with external customers in a dynamic environment.
Articulate with great communication and presentation skills
Team player who can train as well as learn from others.
Fluency in Hebrew and English is essential.
This position is open to all candidates.
 
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1 ימים
Location: Jerusalem
Job Type: Full Time
We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives.
Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud.
Your Arena
Design, develop, and maintain scalable, robust data pipelines and ETL processes
Architect and implement complex data models across various storage solutions
Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
Ensure data quality, consistency, security, and compliance across all data systems
Play a key role in defining and implementing data strategies that drive business value
Contribute to the continuous improvement of our data architecture and processes
Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
Participate in and sometimes lead code reviews to maintain high coding standards
Troubleshoot and resolve complex data-related issues in production environments
Evaluate and recommend new technologies and methodologies to improve our data infrastructure.
Requirements:
5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must
Extensive experience with GraphDB - MUST
Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must
Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must
Designing and implementing data warehouses and data lakes - Must
Strong understanding of data modeling techniques - Must
Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must
Experience with data validation tools such as Pydantic & Great Expectations - Must
Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must
Nice-to-Haves
Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage
Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage
Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage
Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage
Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage
Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage
Understanding of compliance requirements (e.g., GDPR, CCPA) - Advantage
Experience mentoring junior engineers or leading small project teams
Excellent communication skills with the ability to explain complex technical concepts to various audiences
Demonstrated ability to work independently and lead technical initiatives
Relevant certifications in cloud platforms or data technologies.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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Location: Tel Aviv-Yafo
Job Type: Full Time
Required Senior Data Engineer I - GenAI Foundation Models
21679
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
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.
דרישות:
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 המשרה מיועדת לנשים ולגברים כאחד.
 
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Location: Jerusalem
Job Type: Full Time and Temporary
We are seeking a skilled and motivated Data Engineer to join our dynamic team. The ideal candidate will have extensive experience in building and optimizing data pipelines, handling large datasets, and working within cloud-based and on-premise environments.
You will be responsible for designing and implementing efficient, scalable solutions to manage, process, and analyze high volumes of data, ensuring the reliability and performance of our data infrastructure.
What will your job look like:
Design, build, and maintain scalable data pipelines to process large datasets efficiently
Develop and implement data models and architectures that support both real-time and batch data processing
Ensure data integrity, security, and accuracy across all systems
Collaborate with data scientists, analysts, and other engineers to ensure data availability and quality
Optimize data retrieval and storage processes to handle large volumes of data seamlessly
Work with structured, semi-structured, and unstructured data, integrating various data sources
Troubleshoot and resolve data issues, ensuring continuous operation of the data infrastructure
Maintain and enhance ETL processes, ensuring scalability and performance in handling large datasets
Stay up-to-date with industry best practices and emerging technologies related to big data engineering
Requirements:
Bachelors degree in Computer Science, Engineering, or a related field
At least 4 years experience in data engineering, with a focus on large-scale data processing and big data technologies
Strong proficiency in Python
Experience with data pipeline and workflow management tools
Hands-on experience with large-scale data processing frameworks like Apache Spark, Hadoop, or similar
Familiarity with data modeling, ETL processes, and data warehousing concepts like Table formats. Apache Iceberg, or similar
Good knowledge of relational databases (e.g., PostgreSQL, MySQL) and NoSQL databases (e.g., Cassandra, MongoDB)
Experience with AWS-based data lakes, including working with Amazon S3 for storage, querying data using Amazon Athena, and managing datasets stored in Parquet format
Significant ownership ability
Nice to have:
Knowledge of machine learning frameworks and integrating data pipelines for model training and deployment
Experience with version control systems (e.g., Git), CI/CD pipelines, and automation tools
Experience with containerization (Docker, Kubernetes)
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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3 ימים
Job Type: Full Time
Welcome to Chargeflow Chargeflow is at the forefront of fintech + AI innovation, backed by leading venture capital firms. Our mission is to build a fraud-free global commerce ecosystem by leveraging the newest technology, freeing online businesses to focus on their core ideas and growth. We are building the future, and we need you to help shape it. Who We're Looking For - The Dream Maker We're in search of an experienced and skilled Senior Data Engineer to join our growing data team. As part of our data team, you'll be at the forefront of crafting a groundbreaking solution that leverages cutting-edge technology to combat fraud. The ideal candidate will have a strong background in designing and implementing large-scale data solutions, with the potential to grow into a leadership role. This position requires a deep understanding of modern data architectures, cloud technologies, and the ability to drive technical initiatives that align with business objectives. Our ultimate goal is to equip our clients with resilient safeguards against chargebacks, empowering them to safeguard their revenue and optimize their profitability. Join us on this thrilling mission to redefine the battle against fraud. Your Arena
* Design, develop, and maintain scalable, robust data pipelines and ETL processes
* Architect and implement complex data models across various storage solutions
* Collaborate with R&D teams, data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality solutions
* Ensure data quality, consistency, security, and compliance across all data systems
* Play a key role in defining and implementing data strategies that drive business value
* Contribute to the continuous improvement of our data architecture and processes
* Champion and implement data engineering best practices across the R&D organization, serving as a technical expert and go-to resource for data-related questions and challenges
* Participate in and sometimes lead code reviews to maintain high coding standards
* Troubleshoot and resolve complex data-related issues in production environments
* Evaluate and recommend new technologies and methodologies to improve our data infrastructure
Requirements:
What It Takes - Must haves: 5+ years of experience in data engineering, with specific, strong proficiency in Python & software engineering principles - Must
* Extensive experience with GraphDB - MUST
* Extensive experience with AWS, GCP, Azure and cloud-native architectures - Must
* Deep knowledge of both relational (e.g., PostgreSQL) and NoSQL databases - Must
* Designing and implementing data warehouses and data lakes - Must
* Strong understanding of data modeling techniques - Must
* Expertise in data manipulation libraries (e.g., Pandas) and big data processing frameworks - Must
* Experience with data validation tools such as Pydantic & Great Expectations - Must
* Proficiency in writing and maintaining unit tests (e.g., Pytest) and integration tests - Must Nice-to-Haves
* Apache Iceberg - Experience building, managing and maintaining Iceberg lakehouse architecture with S3 storage and AWS Glue catalog - Strong Advantage
* Apache Spark - Proficiency in optimizing Spark jobs, understanding partitioning strategies, and leveraging core framework capabilities for large-scale data processing - Strong Advantage
* Modern data stack tools - DBT, DuckDB, Dagster or any other Data orchestration tool (e.g., Apache Airflow, Prefect) - Advantage
* Designing and developing backend systems, including- RESTful API design and implementation, microservices architecture, event-driven systems, RabbitMQ, Apache Kafka - Advantage
* Containerization technologies- Docker, Kubernetes, and IaC (e.g., Terraform) - Advantage
* Stream processing technologies (e.g., Apache Kafka, Apache Flink) - Advantage
* Understanding of compliance requirements (e.g., GDPR, CCPA) - A
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
Required Data Engineer II - GenAI
20718
The Content Intelligence team is at the forefront of Generative AI innovation, driving solutions for travel-related chatbots, text generation and summarization applications, Q&A systems, and free-text search. Beyond this, the team is building a cutting-edge platform that processes millions of images and textual inputs daily, enriching them with ML capabilities. These enriched datasets power downstream applications, helping personalize the customer experience-for example, selecting and displaying the most relevant images and reviews as customers plan and book their next vacation.
Role Description:
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.
דרישות:
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.#ENG המשרה מיועדת לנשים ולגברים כאחד.
 
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הגשת מועמדותהגש מועמדות
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תודה על שיתוף הפעולה
מודים לך שלקחת חלק בשיפור התוכן שלנו :)
1 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Were looking for a Senior Data Engineer in the Data Collection Ingest team to contribute to the design and coding of data ingestion services & pipelines. This role involves working as part of a team that handles millions of requests per minute across multiple servers, and is responsible for a wide-range of data pipelines, processing billions of events each day.
Why is this role so important?
As the most trusted platform for measuring online behavior, millions of people rely on insights daily as the ground truth for their knowledge of the digital world. Producing these insights requires large scale raw data to be ingested reliably in high scale to provide stable signals for analysis. As a Data Engineer you will have the opportunity to perform hands-on work and own raw data ingestion pipeline end-to-end. Your work will have a direct impact on the quality and reliability of our data and the insights that our products are delivering to our customers.
Requirements:
Has 5+ years of experience in developing code for big data infrastructure. Proficiency in technologies such as: Databricks, Spark, Airflow, Firehose, SQS, or other similar tools.
Proven experience working with high scale on AWS or any other cloud provider. Experience in architecture and design of large-scale and high performance production systems.
Comfortable taking challenges and learning new technologies.
Excellent communication skills with the ability to provide constant dialog between teams.
Ability to take business requirements and translate them to technical alternatives by performing risk management and evaluating tradeoffs.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
Our data engineering team is looking for an experienced professional with expertise in SQL, Python, and strong data modeling skills. In this role, you will be at the heart of our data ecosystem, designing and maintaining cross-engineering initiatives and projects, as well as developing high-quality data pipelines and models that drive decision-making across the organization.

You will play a key role in ensuring data quality, building scalable systems, and supporting cross-functional teams with clean, accurate, and actionable data.



What you will do:

Design, develop, and optimize data services and solutions required to support various company products (like FeatureStore or synthetic data management); Work closely with data analysts, data scientists, engineers, and cross-functional teams to understand data requirements and deliver high-quality solutions.
Design and integrate LLM- and agent-based capabilities into data platforms and services, enabling smarter data operations and AI-driven data products.
Design, develop, and optimize scalable data pipelines to ensure data is clean, accurate, and ready for analysis.
Build and maintain robust data models that support clinical, business intelligence, and operational needs.
Implement and enforce data quality standards, monitoring, and best practices across systems and pipelines.
Manage and optimize large-scale data storage and processing systems to ensure reliability and performance.
Requirements:
5+ years of experience as a Data Engineer / Backend Engineer (with strong emphasis on data processing)
Python Proficiency: Proven ability to build services, solutions, data pipelines, automations, and integration tools using Python.
SQL Expertise: Deep experience in crafting complex queries, optimizing performance, and working with large datasets.
Strong knowledge of data modeling principles and best practices for relational and dimensional data structures.
A passion for maintaining data quality and ensuring trust in business-critical data.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
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8523783
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7 ימים
חברה חסויה
Location: Tel Aviv-Yafo
Job Type: Full Time
We are seeking a Data Engineer to join our dynamic data team. In this role, you will design, build, and maintain robust data systems and infrastructure that support data collection, processing, and analysis. Your expertise will be crucial in developing scalable data pipelines, ensuring data quality, and collaborating with cross-functional teams to deliver actionable insights.

Key Responsibilities:

Design, develop, and maintain scalable ETL processes for data transformation and integration.
Build and manage data pipelines to support analytics and operational needs.
Ensure data accuracy, integrity, and consistency across various sources and systems.
Collaborate with data scientists and analysts to support AI model deployment and data-driven decision-making.
Optimize data storage solutions, including data lakehouses and databases, to enhance performance and scalability..
Monitor and troubleshoot data workflows to maintain system reliability.
Stay updated with emerging technologies and best practices in data engineering.
Requirements:
3+ years of experience in data engineering or a related role within a production environment.
Proficiency in Python and SQL
Experience with both relational (e.g., PostgreSQL) and NoSQL databases (e.g., MongoDB, Elasticsearch).
Familiarity with big data AWS tools and frameworks such as Glue, EMR, Kinesis etc.
Experience with containerization tools like Docker and Kubernetes.
Strong understanding of data warehousing concepts and data modeling.
Excellent problem-solving skills and attention to detail.
Strong communication skills, with the ability to work collaboratively in a team environment.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8524239
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 and Hybrid work
Required Big Data Engineer Team Lead
We are an innovative technology company led by data scientists and engineers devoted to mobile app growth. Our proprietary ad platform is powered by machine learning and is constantly improving its distribution algorithms.
We deliver valuable results and insights for a fast-growing clientele of major app developers using elite programmatic user acquisition and retargeting technologies.
Our state-of-the-art machine learning technology analyzes 50TB of raw data per day to produce millions of ad recommendations in real-time. This data is used to power our machine learning predictions, business-critical metrics, and analytics to power our decision-making.
As a Big Data Team Lead, you will lead a team focused on building scalable, algorithm-heavy data products rather than owning the underlying data infrastructure.
Your team will be responsible for implementing complex business and optimization logic-often incorporating multiple algorithms using Peta-Byte scale data processing (primarily PySpark). A core part of the role is ensuring these data products are explainable, observable, and trusted by Data Science, BI, Product, and business stakeholders.
You will work closely with the Data Infrastructure TL, Data Science, BI, and Product to turn advanced logic into production-grade, transparent, and measurable systems.
Responsibilities:
Lead development of scalable, algorithm-heavy data products using PySpark and Implement and maintain complex, multi-stage data flows with multiple interacting algorithms.
Translate business and algorithmic requirements into clear, testable data logic. Ensuring explainability of outputs through intermediate artifacts, metadata, and documentation & Defining and monitoring; observability signals for data quality, algorithm health, and business impact.
Mentor engineers on reasoning about complex logic, edge cases, and failure modes.
Requirements:
2+ years of experience in technical leadership or leading complex projects.
6+ years of experience as a Data / Backend Engineer in data-intensive systems.
Strong production experience with PySpark.
Excellent SQL skills for complex analysis, validation, and BI-facing data models.
Proven experience implementing complex algorithms and business logic at scale.
Strong understanding of data correctness, edge cases, and validation strategies.
Advantage:
Experience with algorithm explainability and data observability.
Background working closely with Data Science / ML teams.
Experience with large-scale Spark batch or streaming pipelines.
AWS-based data platforms experience.
This position is open to all candidates.
 
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הגשת מועמדותהגש מועמדות
עדכון קורות החיים לפני שליחה
עדכון קורות החיים לפני שליחה
8515719
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