דרושים » דאטה » Data Platform Engineering Lead

Requirements:
5+ years of hands-on experience in backend or data engineering, including 2+ years at a senior level delivering production systems
Strong coding skills in Python, Kotlin, Java or Scala with emphasis on clean, testable, production-ready code
Proven track record designing, building and operating distributed data pipelines and storage (batch or streaming)
Deep experience with relational databases (PostgreSQL preferred) and working knowledge of at least one NoSQL or columnar/analytical store (e.g. SingleStore, ClickHouse, Redshift, BigQuery)
Solid hands-on experience with event-streaming platforms such as Apache Kafka
Familiarity with data-orchestration frameworks such as Airflow
Comfortable with modern CI/CD, observability and infrastructure-as-code practices in a cloud environment (AWS, GCP or Azure)
Ability to break down complex problems, communicate trade-offs clearly, and collaborate effectively with engineers and product partners
Bonus Skills:
Experience building data governance or security/compliance-aware data platforms
Familiarity with Kubernetes, Docker, and infrastructure-as-code tools
Experience with data quality frameworks, lineage, or metadata tooling

Requirements:
5+ years of hands-on experience as a Data Engineer, building and operating production-grade data systems.
3+ years of experience with Spark, SQL, Python, and orchestration tools like Airflow (or similar).
Degree in Computer Science, Engineering, or a related quantitative field.
Proven track record in designing and implementing high-scale ETL pipelines and real-time or batch data workflows.
Deep understanding of data lakehouse and warehouse architectures, dimensional modeling, and performance optimization.
Strong analytical thinking, debugging, and problem-solving skills in complex environments.
Familiarity with infrastructure as code, CI/CD pipelines, and building data-oriented microservices or APIs.
Enthusiasm for AI-driven developer tools such as Cursor.AI or GitHub Copilot.

Requirements:
4+ yeasrs of experience as a Data Engineer
Expertise in designing and developing scalable data pipelines, ETL processes, and data architectures.
Proficiency in Python and SQL, with hands-on experience in big data technologies like Apache Spark and Hadoop.
Advanced knowledge of cloud platforms (AWS, Azure, or GCP) and their associated data services.
Experience working with Imply and Apache Druid for real-time analytics and query optimization.
Strong analytical skills and ability to quickly learn and adapt to new technologies and tools.

Requirements:
Were looking for an experienced and passionate Staff Data Engineer to join our Data Platform group in TLV as a Tech Lead. 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.
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 acros

Requirements:
4+ years of hands-on Data Engineering experience, in a cybersecurity or security-adjacent environment.
Proficiency in Python and SQL, with proven experience handling large or unstructured data.
Familiarity with data warehouse technologies (Snowflake, BigQuery).
Experience with big data infrastructure (Snowflake/Databricks), orchestration tools (Airflow), and cloud platform (AWS).
Solid understanding of data governance, quality assurance, and pipeline observability.
Ability to deliver end-to-end solutionsfrom ingestion to production-ready datasets with minimal supervision.
Nice to Have:
Experience in cybersecurity, threat intelligence, or blockchain data processing.
Experience orchestrating large-scale ETLs in Snowflake
Experience using DBT in production
Knowledge of OLTP databases (e.g., PostgreSQL).

Requirements:
8+ years of hands-on experience in backend or data engineering roles, with 3+ years in senior/staff-level positions
Proven ability to design, implement, and maintain large-scale distributed systems
Strong coding skills in a modern backend language (e.g. Python, Kotlin, Java, Scala), with clean, testable design patterns and production-ready code
Expertise in relational and non-relational databases, especially PostgreSQL and columnar or analytical storage systems (e.g. SingleStore, ClickHouse, Redshift, BigQuery)
Solid experience with streaming platforms like Apache Kafka
Familiarity with data orchestration and pipeline frameworks (e.g. Airflow, Dagster)
Comfortable working in cloud environments (AWS, GCP, or Azure)
Proficiency in infrastructure and deployment workflows (CI/CD, observability, monitoring)
Ability to work across teams and influence architectural decisions at the org level

Requirements:
At least 7 years of experience in backend or data engineering, with a minimum of 3 years in a team lead role.
Experience with development, deployment and automation on AWS - S3, SNS, lambda, batch, dynamo, RDS etc.
Expertise in advanced SQL, including writing complex, efficient queries and building optimized datasets.
Proficient in Python and Python-based data tools.
Working with micro-services on K8S
Proven track record of delivering large-scale, high-quality products
Independent, autodidact with excellent problem solving and passion to learn cutting-edge technologies
Proven ability to lead and mentor a team, manage projects, and collaborate effectively with cross-functional teams.
Outstanding interpersonal skills
Advantage:
Experience in building data stream pipelines and ETL using Big Data frameworks such as Spark and Apache Airflow
Experience with Serverless frameworks
Experience with streaming technologies such as Amazon Kinesis and Apache Kafka.

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills in Java & Python
Experience with TensorFlow a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.

Requirements:
Bachelor's degree in Computer Science, Engineering, or a related field.
Experience: 5+ years of hands-on experience as a Data Engineer or in a similar role.
Data Expertise: Strong understanding of data warehousing concepts, including a deep familiarity with Snowflake.
Technical Skills:
Proficiency in Python and SQL.
Hands-on experience with workflow orchestration tools like Airflow.
Experience with real-time data streaming technologies like Kafka.
Familiarity with container orchestration using Kubernetes (K8s) and dependency management with Poetry.
Cloud Infrastructure: Proven experience with AWS cloud services (e.g., EC2, S3, RDS).

Requirements:
Experience developing large scale systems. Experience with filesystems, server architectures, distributed systems, SQL and No-SQL. Experience with Spark and Airflow / other orchestration platforms is a big plus.
Highly skilled in software engineering methods. 5+ years experience.
Passion for ML engineering and for creating and improving platforms
Experience with designing and supporting ML pipelines and models in production environment
Excellent coding skills in Java & Python
Experience with TensorFlow a big plus
Possess strong problem solving and critical thinking skills
BSc in Computer Science or related field.
Proven ability to work effectively and independently across multiple teams and beyond organizational boundaries
Deep understanding of strong Computer Science fundamentals: object-oriented design, data structures systems, applications programming and multi threading programming
Strong communication skills to be able to present insights and ideas, and excellent English, required to communicate with our global teams.
Bonus points if you have:
Experience in leading Algorithms projects or teams.
Experience in developing models using deep learning techniques and tools
Experience in developing software within a distributed computation framework.