לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER בתל אביב יפו, לחיפוש זה נמצאו 62 משרות

This is a unique opportunity to build and lead a strategic Data & AI capability within a leading consulting firm, shaping its vision, offerings, team, and market presence. The role combines business leadership, solution architecture, and client engagement, helping organizations leverage modern Data & AI platforms to drive transformation and innovation.
Job description
Lead and expand Databricks practice, including strategy, capability development, team growth, and go-to-market initiatives.
Design and oversee enterprise-scale Data & AI solutions, including Lakehouse architectures, data modernization programs, and AI-driven platforms.
Build trusted relationships with senior stakeholders, lead business development efforts, and drive complex technology engagements.
Lead the successful delivery of large-scale Data & AI projects while mentoring and developing high-performing teams.

We're hiring a Data Engineer to architect and own the systems that turn raw signal from merchants, customers, and experiments into something the whole company can build on.
Data is at the heart of everything we do - it powers our AI models, drives merchant-facing analytics, and informs how we make product decisions every day.
This is a high-ownership role for someone who wants to shape data architecture from the ground up- not inherit someone else's roadmap. You'll be the person who makes sure our data is fast, trustworthy, and easy for every team to use.
What You'll Do:
Architect and build scalable data pipelines processing millions of events daily from merchant stores, product usage, experiments, and third-party integrations
Own our data warehouse strategy end-to-end- reliability, performance, and scalability as we grow
Define our event architecture and set the standards for how the company captures and models product and business data
Build data quality practices- monitoring, validation, testing, and alerting- that the rest of the team can trust
Partner directly with Product and Engineering to unlock the data behind our AI features, merchant analytics, and experimentation
Build self-service tooling so other teams can query and analyze data without depending on you as a bottleneck
Set the bar for data modeling, orchestration, and documentation across the org

We are seeking an experienced Solutions Data Engineer who possess both technical depth and strong interpersonal skills to partner with internal and external teams to develop scalable, flexible, and cutting-edge solutions. Solutions Engineers collaborate with operations and business development to help craft solutions to meet customer business problems.
A Solutions Engineer works to balance various aspects of the project, from safety to design. Additionally, a Solutions Engineer researches advanced technology regarding best practices in the field and seek to find cost-effective solutions.
Job Description:
Were looking for a Solutions Engineer with deep experience in Big Data technologies, real-time data pipelines, and scalable infrastructure-someone whos been delivering critical systems under pressure, and knows what it takes to bring complex data architectures to life. This isnt just about checking boxes on tech stacks-its about solving real-world data problems, collaborating with smart people, and building robust, future-proof solutions.
In this role, youll partner closely with engineering, product, and customers to design and deliver high-impact systems that move, transform, and serve data at scale. Youll help customers architect pipelines that are not only performant and cost-efficient but also easy to operate and evolve.
We want someone whos comfortable switching hats between low-level debugging, high-level architecture, and communicating clearly with stakeholders of all technical levels.
Key Responsibilities:
Build distributed data pipelines using technologies like Kafka, Spark (batch & streaming), Python, Trino, Airflow, and S3-compatible data lakes-designed for scale, modularity, and seamless integration across real-time and batch workloads.
Design, deploy, and troubleshoot hybrid cloud/on-prem environments using Terraform, Docker, Kubernetes, and CI/CD automation tools.
Implement event-driven and serverless workflows with precise control over latency, throughput, and fault tolerance trade-offs.
Create technical guides, architecture docs, and demo pipelines to support onboarding, evangelize best practices, and accelerate adoption across engineering, product, and customer-facing teams.
Integrate data validation, observability tools, and governance directly into the pipeline lifecycle.
Own end-to-end platform lifecycle: ingestion → transformation → storage (Parquet/ORC on S3) → compute layer (Trino/Spark).
Benchmark and tune storage backends (S3/NFS/SMB) and compute layers for throughput, latency, and scalability using production datasets.
Work cross-functionally with R&D to push performance limits across interactive, streaming, and ML-ready analytics workloads.
Operate and debug object store-backed data lake infrastructure, enabling schema-on-read access, high-throughput ingestion, advanced searching strategies, and performance tuning for large-scale workloads.

In your role as a Data Engineer at Tikal, you'll be actively engaged in the most fascinating and demanding projects for our clients. Handling high-scale operations, heavy traffic, stringent SLAs, and massive data volumes is just the starting point. Our leadership in the realms of Big Data, Streaming Data, and Complex Event Processing (CEP) stems from our adept use of cutting-edge, optimal technologies.

Responsibilities:
Apply software-engineering methods and best practices (Medallion Architecture) in Data Lake management, using tools like DBT.
Develop Data pipelines to ingest and transform data.
Manage and enhance orchestrated pipelines across company
Data Modeling: Developing data models to ensure efficient storage, retrieval, and processing of data, often involving schema design for NoSQL databases, data lakes, and data warehouses. This will also include catalogs of data.
Scalability: Ensuring that the big data architecture can scale horizontally to handle large volumes of data and high traffic loads.
Data Security: Implementing security measures to protect sensitive data, including encryption, access controls, and data masking.
Data Governance: Establishing data governance policies to ensure data quality, compliance with regulations, and data lineage.

We're hiring a Director of Data to lead data function and build our data into a
real competitive moat. You'll report to the CPO, manage and grow our lean data team, and
partner across the leadership table. The role is roughly 70% Build & Operate, 30% Lead &
Influence in year one, shifting toward 50/50 as the team scales.
What you'll do:
Lead and grow our data team. Set direction, raise the bar, make their job better.
Make self-service analytics real across First Connect, so every leader gets to their
answers without queuing behind the data team.
Create a contracts-based partnership with the engineering teams producing source data.
Build a core proprietary data asset that powers our internal and partner-facing
experiences and anchors real conversations with our carriers.
Own the data infrastructure roadmap and the question of how we evolve our data
engineering investment over the next 12-24 months.
Define how AI gets leveraged across our data stack and analytical workflows.
Be the data partner the leadership team actually wants to call.

As a Senior Software Engineer your role will be to:

Play a key role in the design and architecture of cutting-edge, innovative data systems.
Develop and maintain a multi-tenant environment for our advanced measurement solutions.
Build and manage cloud-based, distributed computing environments to support scalable, high-performance operations.
Design and implement robust ETL workflows, integrating multiple data sources for cleaning, transformation, aggregation, and querying.
Troubleshoot and resolve complex issues related to data integration, storage, and retrieval.
Architect and build big data solutions capable of managing and automating the processing of tens of terabytes.
Optimize database performance and streamline query execution in large-scale environments.
Collaborate closely with Data Scientists to align technical solutions with data-driven objectives.

As a Senior Software Engineer your role will be to:

Play a key role in the design and architecture of cutting-edge, innovative data systems.
Develop and maintain a multi-tenant environment for our advanced measurement solutions.
Build and manage cloud-based, distributed computing environments to support scalable, high-performance operations.
Design and implement robust ETL workflows, integrating multiple data sources for cleaning, transformation, aggregation, and querying.
Troubleshoot and resolve complex issues related to data integration, storage, and retrieval.
Architect and build big data solutions capable of managing and automating the processing of tens of terabytes.
Optimize database performance and streamline query execution in large-scale environments.
Collaborate closely with Data Scientists to align technical solutions with data-driven objectives.

Required Data Engineering Lead
Why this role matters:
Data isn't just for dashboards - it's the nervous system of our future products. As we expand into smart lighting (Oasis) and living tech (Easyplant), we need to process massive streams of IoT signals and power real-time AI. You won't just maintain a warehouse; you will architect the platform that connects our physical products to the digital world.
What youll do:
Build the "Brain": Architect the next-gen data platform capable of handling high-volume IoT streams and integrating AI capabilities into our daily operations.
Code the Core: This is a hands-on role. You wont just manage; youll be deep in Python, DBT, and Airflow, building and optimizing the pipelines yourself.
Scale for Complexity: We are growing from one product to a multi-brand ecosystem. You will ensure our data infrastructure evolves to support diverse business lines without becoming a bottleneck.
Democratize Insights: Build a system so robust and intuitive that every engineer, product manager, and marketer can self-serve the data they need to build better products.

We are looking for a Backend Engineer with deep data engineering expertise to build and evolve the systems that power product, analytics, experimentation, and AI development.
You will work across production backend services and data infrastructure, taking technical ownership of the full data lifecycle - from event ingestion and real-time processing to orchestration, modeling, quality, and reliable data access. This role combines hands-on backend development with ownership of shared data platform, working closely with backend, frontend, AI, DevOps, analytics, and product teams.
What you'll do:
Build and maintain production-grade Python and Java backend services, APIs, and reactive data-processing pipelines with clear interfaces, resilient failure handling, and comprehensive observability.
Own and evolve batch and streaming data pipelines supporting product analytics, learner insights, experimentation, and AI model training.
Design and maintain trusted data models, shared metrics, and semantic-layer business logic across the analytical data platform.
Define and enforce standards for data contracts, testing, lineage, freshness, and observability.
Develop reliable approaches to schema evolution, backfills, replay, workload distribution, and failure recovery.
Collaborate with DevOps, backend, frontend, AI, analytics, and product teams to deliver reusable data capabilities and maintain clear system boundaries.

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 at our company, 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 our company understands and improves its 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 company's 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 our company operates
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.

We are looking for a highly skilled Senior Data Platform Engineer to join our Data Platform team and play a key role in designing, building, and evolving the companys data infrastructure.

This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the companys future growth.

This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.


What Youll Do
Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platforms streaming capabilities.
Design and implement data solutions for all application requirements in a distributed microservices environment
Develop and optimize large-scale data pipelines for batch and streaming use cases.
Ensure data quality, compliance, and governance.
Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.

We are seeking a Senior Backend Engineer - Data Platform to join our expanding team and play a crucial role in designing, building, and maintaining robust and scalable data pipelines and infrastructure. In this role, you will directly enable data-driven decision-making and support the development and deployment of AI/ML products that power Health.
Youll collaborate closely with engineering, product, and data science teams to ensure our data systems are high-quality, resilient, and scalable as we grow. As a Senior Backend Engineer on our Data Platform team, you will drive efforts to deliver reliable, efficient, and consistent data services across the organization. You will also help enable the rapid development and deployment of advanced features, insights, and AI-driven capabilities that improve outcomes for clinicians and clients.

Required Data Platform Engineering Team Leader
As a Data Platform Engineering Team Leader on the Infrastructure R&D Department in our Tel Aviv office, youll lead the engineering team behind the data platform powering our reporting, billing, experimentation, ML training, and revenue optimization. Youll shape the technical direction of one of our most critical platforms, grow exceptional engineers, and solve complex data infrastructure challenges at massive scale-building systems that are reliable, scalable, and easy to use.
How youll make an impact:
Lead, mentor, and grow a team of talented software engineers while fostering technical excellence and ownership.
Define the teams technical strategy, roadmap, and architecture for one of our core data platforms.
Own the reliability, scalability, and performance of the data pipelines powering reporting, billing, experimentation, and ML training.
Partner with engineering, product, finance, and ML teams to align priorities and deliver high-impact platform capabilities.
Drive the adoption of modern data technologies and AI-powered engineering practices to improve developer productivity and platform evolution.
Stay hands-on by reviewing architecture, code, and technical designs, while helping the team solve complex engineering challenges.
Guide the evolution of the Spark SQL platform and shared data infrastructure used across R&D.
Represent the team in architecture reviews, hiring, incident postmortems, and technical forums.