דרושים » תוכנה » Data Engineer

We are looking for a Senior Data Engineer to build and scale the data foundation behind platform and products. You will own complex data end-to-end - from ingestion and transformation through modeling, quality, observability, and production delivery.
This is a hands-on senior IC role for a strong builder who can solve difficult data problems independently, set a high technical bar, and collaborate closely with engineering, DS, and product. You will turn large, fragmented datasets into reliable, reusable capabilities that power every product.
Responsibilities
Build and own scalable data pipelines- Design, implement, and operate robust pipelines for high-volume structured and unstructured data, with validation, monitoring, lineage, and recovery built in.
Scale the platform for growth- A key near-term initiative is re-architecting the system to support a significantly larger customer base. You will own performance and cost-efficiency across pipelines and services, keeping reliability and operating costs under control as the platform scales.
Build across the stack- This is not a pipelines-only role. You will also write backend services and some frontend, including the internal backoffice the team runs on. We hire builders, not narrow specialists.
Own the core data tables- Own schema design and evolution, data contracts, and the modeling standards the team follows - naming, shared dimensions, normalization, documentation. Be accountable when a table is wrong, late, or drifting.
Level up the teams data work- Pair with and advise software engineers and data scientists on Spark, SQL, and modeling, and help turn notebook-grade code into production-grade pipelines.
Partner cross-functionally- Translate product, client, compliance, and business requirements into clear technical designs and dependable production systems.

We are looking for a Data Engineer to help build and scale the data platform behind our search quality, ML pipelines, product analytics, and business operations.
In this role, you will contribute across the full data lifecycle: ingesting data from production systems, designing and evolving our data warehouse, building batch and streaming pipelines, and making high-quality datasets available to researchers, engineers, analysts, and product teams across the company.
The platform spans tens of terabytes and ingests data from tens of proprietary and third-party sources - including our search engine and its components, CRM, billing, identity, and product analytics across multi-region production environments. Around 100 internal users rely on it daily.
You will work closely with engineers and stakeholders across the company, contribute to architectural and modeling decisions, and help improve the reliability, usability, and scalability of the data platform as it grows.

In this position, your responsibility will be to:
Contribute to the design, development, and operation of Tavily's data platform - from real-time ingestion through data warehouse medallion layers to consumer-facing datasets and dashboards.
Build and maintain reliable batch and streaming pipelines that ingest data from production services and external systems.
Design and evolve scalable, analytics-ready data models in the data warehouse.
Work closely with engineers across the company to ensure data produced by production systems is reliable, well-structured, and usable downstream.
Improve observability across the data platform, including data quality checks, freshness monitoring, lineage, schema evolution, and cost controls.
Partner with researchers, engineers, analysts, finance, and product managers to deliver trustworthy datasets for product, search quality, ML, and GTM analytics.
Contribute to defining the objects, entities, and relationships that represent Tavily's search domain - including agent inputs, URLs, chunks, agent sessions, crawls, and the connections between them - and translate them into clean, queryable data models.
Improve engineering practices around testing, documentation, deployment, and incident response.
Investigate and resolve production data issues, including broken pipelines, corrupted datasets, schema changes, and large-scale backfills.
Contribute to technical standards and best practices for data engineering across the company.
Help maintain high standards of data quality, integrity, security, and governance across environments.

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.

Were looking for an experienced and passionate Data Group Tech Lead, Staff Engineer to join our Data Platform group in TLV. 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 companys data ecosystem.
The groups mission is to build a state-of-the-art Data Platform that drives our company 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 at our company: 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 our company 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.

We are seeking talented and passionate Senior Data Engineer to join our Data team. In this pivotal role, you will be instrumental in designing, building, and optimizing the critical data infrastructure that underpins innovative creative intelligence platform. You will tackle complex data challenges, ensuring our systems are robust, scalable, and capable of delivering high-quality data to power our advanced AI models, customer-facing analytics, and internal business intelligence. This is an opportunity to make a significant impact on our product, contribute to a data-driven culture, and help solve fascinating problems at the intersection of data, AI, and marketing technology.

Key Responsibilities
Architect & Develop Data Pipelines: Design, implement, and maintain sophisticated, end-to-end data pipelines for ingesting, processing, validating, and transforming large-scale, diverse datasets.
Manage Data Orchestration: Implement and manage robust workflow orchestration for complex, multi-step data processes, ensuring reliability and visibility.
Advanced Data Transformation & Modeling: Develop and optimize complex data transformations using advanced SQL and other data manipulation techniques. Contribute to the design and implementation of effective data models for analytical and operational use.
Ensure Data Quality & Platform Reliability: Establish and improve processes for data quality assurance, monitoring, alerting, and performance optimization across the data platform. Proactively identify and resolve data integrity and pipeline issues.
Cross-Functional Collaboration: Partner closely with AI engineers, product managers, developers, customer success and other stakeholders to understand data needs, integrate data solutions, and deliver features that provide exceptional value.
Drive Data Platform Excellence: Contribute to the evolution of our data architecture, champion best practices in data engineering (e.g., DataOps principles), and evaluate emerging technologies to enhance platform capabilities, stability, and cost-effectiveness.
Foster a Culture of Learning & Impact: Actively share knowledge, contribute to team growth, and maintain a strong focus on how data engineering efforts translate into tangible product and business outcomes.

We are looking for an experienced and visionary Data Engineer to help design, build, and scale our BI platform.
In this role, you will be responsible for developing our data analytics platform - enabling scalable data pipelines and robust data modeling to support real-time and batch analytics to provide insights that serve both business intelligence and product needs.
You will be part of the R&D team, collaborating closely with engineers, analysts, and product managers to deliver a modern data architecture that supports internal dashboards and future-facing operational analytics.
If you enjoy turning raw data into powerful insights and owning the full data lifecycle, this role is for you!
Responsibilities:
Take full ownership of the design and implementation of a scalable and efficient BI data infrastructure, ensuring high performance, reliability, and security.
Design and architect data products, from ingestion to transformation, modeling, storage, and access.
Build and maintain ETL/ELT pipelines, batch and real-time, to support analytics, reporting, and product integrations.
Establish and enforce best practices for data quality, lineage, observability, and governance to ensure accuracy and consistency.
Integrate modern tools and frameworks such as Airflow, Databricks, Power BI, and streaming platforms.
Collaborate cross-functional with product, engineering, and analytics teams to translate business needs into data infrastructure.
Promote a data-driven culture - be an advocate for data-driven decision-making across the company by empowering stakeholders with reliable and self-service data access.

Were looking for a Data Engineer to join our company. This is a hands-on, cross-functional role focused on owning and improving our data quality, pipeline reliability, and modeling infrastructure. Youll be responsible for managing and optimizing our DBT models, ETL processes, and data connectors - and will work closely with product, operations, and engineering teams to ensure data is accurate, consistent, and accessible.

You should be someone who thrives on autonomy, takes pride in clean and scalable solutions, and enjoys helping others get the data they need.

In this role you will
Architect our entire DBT project and data warehouse structure completely from scratch-a rare, high-impact opportunity
Lead data modeling efforts: Translating business needs into scalable, reliable data models
Build and monitor data pipelines and connectors from various internal and external systems
Ensure high standards of data quality, consistency, and documentation
Collaborate with engineering, product, and operations teams to understand needs and build data solutions
Proactively detect data issues and work to resolve them
Help define and improve internal data best practices and standards
Support data governance efforts and advocate for trustworthy, well-modeled data
You will be one of the pioneers of a new team - passion & energy is required

We're hiring a Director of Data to lead our company's 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.
About us
we are an insurance marketplace and aggregator. We connect thousands of
independent insurance agencies with a wide network of carriers, MGAs, and wholesalers. We
sit at a vantage point neither agents nor carriers have on their own, and turning that asymmetric
view into proprietary intelligence is one of the most important things we'll do over the next
several years.
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 our company, 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.

We are looking for a Senior Data Architect to help define and evolve the data architecture of our SaaS platform and core products. You will work closely with product, delivery, and engineering squads to design scalable, reliable data systems, set technical direction for how data is ingested, modeled, stored, and served, and guide teams in making high-quality architectural decisions that balance delivery speed with long-term sustainability.
This is a hands-on, senior technical leadership role: you will spend most of your time shaping data architectures with teams, reviewing data models, pipelines and critical code, and driving shared standards and patterns across the organization, all in an advanced agentic environment.
Responsibilities:
Define and evolve the data architecture for key domains (ingestion, ELT/ETL, data modeling, storage, APIs, integration, observability, governance, and security), including owning the lakehouse/medallion architecture (bronze/silver/gold) and the data flows that move data across layers at scale.
Translate business and product requirements into pragmatic data designs, data contracts, and architecture roadmaps; create and maintain architecture artefacts (data flow/lineage diagrams, ADRs, reference implementations, modeling guidelines).
Evaluate design options and technology choices, articulate trade-offs, and lead decision-making with stakeholders; push forward the agentic mindset and implementation across the data platform.
Partner with squad leads and senior engineers to design data solutions, break down complex problems, and keep implementations aligned with the target architecture; participate in design/tech reviews to ensure NFRs (performance, scalability, data quality, resilience, security, operability) are addressed early.
Provide hands-on support where it matters most: spike and prototype critical data flows, review complex PRs, and help debug tricky production data and pipeline issues.
Collaborate with Product to shape technical feasibility, sequencing, and scope for data-driven roadmap items; communicate complex technical topics in simple language to non-technical stakeholders.
Define and promote data architecture principles, modeling conventions, coding standards, and reusable patterns (shared transformations, libraries, datasets, services) to reduce duplication and technical debt; drive adoption of shared platform capabilities (observability, CI/CD, orchestration, governance, DevOps tooling) across squads.
Ensure data architectures are observable, operable, and resilient by design; partner with DevOps/SRE on deployment, monitoring, data quality, and incident response; identify areas of high technical debt or architectural risk and lead remediation initiatives; define and track technical KPIs tied to architecture decisions.
Act as a technical mentor for senior engineers and tech leads, fostering a culture of thoughtful design, documentation, and constructive technical debate; lead by influence- help teams make better decisions instead of making every decision for them.

We're looking for a Data Warehouse Tech Lead to drive the technical vision and execution of our data infrastructure that powers decision-making across all of our company.
You'll lead both the technology and the business coordination for our data warehouse - architecting scalable solutions while working closely with stakeholders and data providers to ensure our platform serves the entire organization's needs. This role combines deep technical leadership with strategic business partnership as we build our company's next-generation data stack.
We believe three things matter for every role at our company: 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 you'll
Lead technical architecture - design and develop scalable data warehouse solutions that support multiple products and serve the entire organization's analytics needs
Manage the technical roadmap - set strategy and guide execution for the Data Warehouse team, ensuring our platform evolves with business requirements
Drive business process coordination - translate business needs into technical requirements while establishing clear data contracts with R&D, Analytics, and external data providers
Establish and implement best practices - set technical standards for data warehouse architecture, performance tuning, and development methodologies that guide the entire team's approach to building scalable data solutions
Create and maintain sustainable data pipelines - build resilient systems capable of handling unstructured data and managing an evolving schema registry across diverse data sources
Implement advanced data modeling - create robust data structures using methodologies like dimensional modeling, and optimize ETL/ELT processes for our semantic layer
Establish data quality standards - build processes for schema evaluation, anomaly detection, and monitoring data completeness and freshness across all sources
Lead cross-team collaboration - work directly with Data Engineers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers to align technical solutions with business goals.