Data Engineer jobs in Herzliya

Description Upstream delivers a cloud-based, AI-powered behavioral intelligence platform for physical AI and smart mobility. Upstream empowers customers with advanced AI-driven cybersecurity solutions, including detection and response (XDR), AI Security, quality and operational intelligence, cyber threat intel, SOC services, and more. Upstream is looking for an experienced Platform Engineer to join our core platform engineering team, focusing on developing and maintaining our AI-powered automotive data management platform. As a Platform Engineer, you will design, build, and operate scalable, production-grade data and ML platform components, ensuring high reliability and performance. You will work closely with our Data Engineering and Data Science teams to develop and enhance our Iceberg-based data platform, including a data lake, query engine, and MLOps tools, providing a solid AI-ready foundation for our automotive solutions. These solutions support millions of connected vehicles worldwide, focusing on cybersecurity (XDR), vehicle quality, and operational intelligence. You will work with technologies such as Iceberg, Trino, Prefect, GitHub Actions, Kubernetes, JupyterHub, MLflow, and dbt. This role is full-time and is Herzliya, Israel-based. Responsibilities • Design, build, and maintain scalable data pipelines to ingest and transform batch data on our data lake, enabling analytics and ML with strong data quality, governance, observability, and CI/CD. • Build and expand our foundational data infrastructure, including our data lake, analytics engine, and batch processing frameworks. • Create robust infrastructure to enable automated pipelines that will ingest and process data into our analytical platforms, leveraging open-source, cloud-agnostic frameworks and toolsets. • Develop and maintain our data lake layouts and architectures for efficient data access and advanced analytics. • Develop and manage orchestration tools, governance tools, data discovery tools, and more. • Work with other team members of the engineering group, including data architects, data analysts, and data scientists, to provide solutions using a use case-based approach that drives the construction of technical data flows. • End-to-end ownership mindset with a proactive, production-first approach Requirements • BSc/BA in Computer Science, Engineering or a related field • At least 4 years of experience with designing and building data pipelines, analytical tools and data lakes • Experience with the data engineering tech stack: ETL & orchestration tools (e.g. Airflow, Argo, Prefect), and distributed data processing tools (e.g Spark, Kafka, Presto) • Experience with Python is a must • Experience working with open-source products - Advantage • Experience working in a containerized environment (e.g. k8s) - Advantage • Development experience, using a general purpose programming language (Java, Scala, Kotlin, Go, etc.) - Advantage Upstream is an equal opportunity employer. All candidates for employment will be considered without regard to race, color, religion, sex, national origin, physical or mental disability, veteran status, or any other basis protected by applicable federal, state or local law.

AppsFlyer processes 150+ billion events across its platform, and our Web Attribution team is at the center of extending that power beyond mobile. We build the product that shows advertisers which campaigns really drive results on the web. We attribute every web user journey, from first click to conversion, across thousands of apps and billions of sessions. We're looking for a Senior Data Engineer to own the technical direction of our pipelines. You'll be the team's go-to data engineering expert and a key knowledge holder: the person the team turns to for Spark, data modeling, and the hardest pipeline problems. You'll lead the team's design work and work closely with the team lead on planning and technical priorities. You'll shape the product that advertisers and marketers rely on every day. What you’ll do • Build & Own End-to-End Pipelines: Build and improve pipelines that process billions of web events (sessions, in-app events, conversions) with strict freshness and accuracy SLAs, from ingestion through distributed processing to the serving layer. • Lead Design & Architecture: Own the technical design of the team's pipelines, from spec to production. Write design docs, review the team's designs, and make the key trade-offs, such as what runs in SQL and what runs in Spark. Work with the group's architects on cross-team designs. • Drive Technical Planning: Work with the team lead on the roadmap, planning, and priorities. Break large projects into clear deliverables. Represent the team in technical discussions with Product, R&D, and partner teams. Own production incidents end-to-end and turn them into lasting fixes. What you have • 6+ years in Data / Big Data Engineering, including building and running production systems at scale. • B.Sc. in Computer Science or equivalent. • Deep, hands-on Apache Spark experience: you understand execution plans, partitioning, and memory management, and you know how to debug skew and performance problems at scale. • Deep experience with a cloud analytical warehouse (BigQuery, Snowflake, Redshift, or Databricks SQL) as both a processing and serving layer. BigQuery is a strong advantage. • A proven track record in data-system design: you've written design docs, made trade-offs between cost, latency, and correctness, and taken designs all the way to production. • Experience with workflow orchestration (e.g., Airflow) and cloud environments at production scale. GCP preferred. • Strong programming fundamentals: clean, testable, production-grade code. Scala preferred; Python for orchestration. • A natural instinct for data quality: you think about edge cases, dedup logic, and "what happens when this field is null" before anyone asks. • Hands-on use of AI tools in your daily engineering work, and a clear view of where AI helps data engineering and where it doesn't. Bonus points • Experience building or maintaining attribution / AdTech data systems. • Advanced Scala or functional programming experience. • Experience with attribution models (last-click, multi-touch, view-through). • Experience with SQL-based transformation frameworks (Dataform, dbt) or data-mesh / data-product platforms. • Experience with Kafka or streaming systems. • Experience running LLMs or ML pipelines in production. • Being introduced by an AppsFlyer team member As a global company operating from 25 offices across 19 countries, we reflect the human mosaic of the diverse and multicultural world in which we live. We ensure equal opportunities for all of our employees and promote the recruitment of diverse talents to our global teams without consideration of race, gender, culture, or sexual orientation. We value and encourage curiosity, diversity, and innovation from all our employees, customers, and partners. “As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO

Description CodeValue is looking for an experienced, hands-on Senior Backend Engineer with strong expertise in Python and data-intensive systems to join our development team. In this role, you will design, develop, and maintain backend services and reliable data pipelines, build integrations with external systems, and work with modern cloud technologies and AI-powered development tools. You will collaborate closely with engineering, data, and implementation teams to deliver scalable, high-quality software solutions. Key Responsibilities • Design, develop, and maintain backend services and production-grade data pipelines. • Build and operate batch and event-driven ETL processes, including data transformation, validation, and schema management. • Design and maintain data models and schemas that serve as a reliable source of truth across systems. • Develop integrations with external systems and data sources, including API-based integrations and structured data files. • Build reusable integration frameworks and tools to streamline data onboarding, validation, and troubleshooting. • Work with relational and document databases, ensuring data consistency, reliability, and performance. • Implement monitoring, logging, alerting, and observability for production systems. • Ensure data security, auditability, and appropriate access controls in compliance-sensitive environments. • Collaborate with backend, DevOps, data, and other cross-functional teams throughout the software development lifecycle. • Leverage AI-assisted development tools to improve engineering productivity and code quality. Requirements • 5+ years of hands-on experience in backend software development, with significant experience building data pipelines or data-intensive systems. • Strong proficiency in Python, including asynchronous programming and modern web frameworks such as FastAPI. • Proven experience designing, developing, and maintaining production data pipelines, including batch and event-driven ETL. • Hands-on experience with AWS services such as S3, SQS, Lambda, RDS/PostgreSQL, and DynamoDB. • Experience deploying and maintaining containerized services in Kubernetes environments. • Strong SQL skills and practical experience with relational and document databases. • Experience with Python data-processing tools such as pandas and Parquet, as well as schema validation libraries such as Pydantic. • Experience owning production systems end to end, including monitoring, alerting, troubleshooting, and incident handling. • Experience using AI-powered coding tools such as Claude Code or Cursor as part of the daily development workflow. • Experience working in Agile development environments. • Bachelor's or Master's degree in Computer Science or a related field. • Strong analytical and problem-solving skills, a data-oriented mindset, and a proactive approach to delivery. • Excellent written and verbal English communication skills. Advantages • Experience working with healthcare data standards and integrations, such as HL7v2, FHIR, Epic, or Oracle Health. • Experience integrating workforce management or scheduling platforms, such as UKG or QGenda. • Familiarity with handling sensitive data and security frameworks such as HIPAA or SOC 2. • Experience building multi-tenant SaaS platforms. • Experience with data governance, audit logging, and tenant isolation.