דרושים » דאטה » Mid-Senior BI Developer

Were looking for an experienced Data Engineer to join our DataWarehouse team in TLV.
In this role, you will play a pivotal role in the Data Platform organization, leading the design, development, and maintenance of our data warehouse. In your day-to-day, youll work on data models and Backend BI solutions that empower stakeholders across the company and contribute to informed decision-making processes all while leveraging your extensive experience in business intelligence.
This is an excellent opportunity to be part of establishing our state-of-the-art data stack, implementing cutting-edge technologies in a cloud environment.
We believe three things matter for every role: 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:
Lead the design and development of scalable and efficient data warehouse and BI solutions that align with organizational goals and requirements
Utilize advanced data modeling techniques to create robust data structures supporting reporting and analytics needs
Implement ETL/ELT processes to assist in the extraction, transformation, and loading of data from various sources into the semantic layer
Develop processes to enforce schema evaluation, cover anomaly detection, and monitor data completeness and freshness
Identify and address performance bottlenecks within our data warehouse, optimize queries and processes, and enhance data retrieval efficiency
Implement best practices for data warehouse and database performance tuning
Conduct thorough testing of data applications and implement robust validation processes
Collaborate with Data Infra Engineers, Developers, ML Platform Engineers, Data Scientists, Analysts, and Product Managers

We're hiring a Data Engineer to join our growing team of analytics experts in order to help & lead the build-out of our data integration and pipeline processes, tools and platform.
The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
The right candidate must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our companys data architecture to support our next generation of products and data initiatives.
In this role, you will be responsible for:
Create ELT/Streaming processes and SQL queries to bring data to/from the data warehouse and other data sources.
Establish scalable, efficient, automated processes for large-scale data analyses.
Support the development of performance dashboards & data sets that will generate the right insight.
Work with business owners and partners to build data sets that answer their specific business questions.
Collaborates with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decision-making across the organization.
Works closely with all business units and engineering teams to develop a strategy for long-term data platform architecture.
Own the data lake pipelines, maintenance, improvements and schema.

Were looking for a Senior BI Data Engineer to join our BI team and take end-to-end ownership of high-impact analytics foundations. This role sits at the core of how our company measures success, makes decisions, and scales - turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.
Youll design and evolve data models, pipelines, and the BI layer, work closely with Data Science and business stakeholders, and help raise the bar for analytics engineering across the company.
Hands-on experience using GenAI to improve analytics engineering workflows, automate development processes, and increase delivery speed is a must for this role.
This role is based in Tel Aviv. We work in a hybrid model, with 3 days a week in the office.
This might be for you if:
You enjoy owning data foundations end to end - from raw data to semantic layers
You like turning ambiguous business questions into clear, governed metrics
You care about data quality, performance, and trust at scale
You enjoy mentoring, setting standards, and leading by example
You actively leverage AI tools to improve development speed and analytical accuracy.

looking for a Data Engineer to help build and scale our analytics data infrastructure. In this role, you will work closely with analysts and business stakeholders to design reliable data models and support the development of a centralized semantic layer used across the company.

You will play a key role in improving the structure, reliability, and usability of our data stack. This includes building and maintaining dbt models, supporting data pipelines, and ensuring analysts have access to clean, well-documented, and consistent data.

This role is ideal for someone who enjoys working at the intersection of data engineering and analytics - translating business needs into scalable data models and enabling teams to move faster with trusted data.

Responsibilities

Design and implement data models that support analytics across key business domains such as GTM, CX, and Finance
Build and maintain transformation workflows using dbt
Work closely with analysts to translate business questions into scalable and reusable data models
Help define and implement a structured semantic layer that enables consistent metrics across the company
Improve the reliability and clarity of the analytics data stack by centralizing logic into well-designed data models
Support the ingestion and transformation of data from various sources using tools such as Fivetran and Airbyte
Contribute to improving data quality, monitoring, and documentation practices
Help establish best practices for analytics modeling and data usage across teams
Actively leverage AI tools (e.g. Cursor, LLM-based assistants) to improve development speed, data modeling, and data workflows

We are looking for a hands on, proactive, and impact driven Senior Business Analyst to join our data team. In this role, youll shape how the company measures success and help embed a strong data driven culture across every domain, from business operations to product, finance, and beyond.

This is an opportunity for someone who thrives in dynamic, fast changing environments, loves building from scratch, and is just as comfortable running deep analyses and leading cross functional measurement discussions as they are partnering with data engineering to design scalable data models that empower the entire organization.

In this role you will
Collaborate with cross functional teams to understand business objectives and develop data driven solutions
Lead measurement and metric discussions with diverse stakeholders, translating needs into clear, consistent, and actionable definitions
Conduct deep dive analyses to uncover insights and deliver impactful recommendations
Partner with data engineering to design scalable data models and improve data accessibility
Build clear, intuitive dashboards and reports to track performance and enable self serve analytics
Proactively monitor business metrics and provide timely insights to optimize operations and identify opportunities
Promote a data driven culture by empowering teams to use data confidently in decision making
Mentor teammates and contribute to the growth and maturity of the data function

we are looking for a Senior Data Engineer I.
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.
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Were looking for a Senior Data Engineer to own high-impact data products from architecture through production deployment, monitoring, and continuous improvement. This isnt a pure infrastructure role - youll combine strong engineering with product thinking, operational excellence, and awareness of data quality, cost, and business impact.
You will design, implement, test, deploy, and maintain production-grade data products - pipelines, transformation layers, data quality and reliability systems - using tools like DBT (on Spark) and Databricks. Youll apply best practices in Python and SQL to build scalable and maintainable data transformations, and leverage technologies like LLMs and GenAI to create innovative solutions for real business problems.
This role is ideal for someone who wants technical leadership responsibilities in an AI-first engineering culture - we use LLMs, GenAI, and AI-native development tools as core parts of our daily workflow.
Key Responsibilities:
Act as a technical leader within the team - raise engineering standards, drive strong architectural choices, and improve how we build
Own data products end-to-end: design, development, deployment, monitoring, and iteration
Work closely with senior leadership to translate strategic goals into scalable data solutions
Develop and maintain production ETL/ELT pipelines using DBT (on Spark) and orchestrated workflows in Databricks
Build monitoring, alerting, and testing pipelines to ensure reliability and performance in production
Evaluate and introduce new technologies - including AI-native development tools - and integrate the ones that create real impact
Collaborate with customers and external data providers - gathering requirements and making product decisions.
Mentor team members through code reviews, pairing, and knowledge sharing

At our company, Israels first fully digital bank, were building the technology that powers a new era of intuitive, transparent, people-first banking. As our platform grows and our services expand, were looking for a team leader to lead a data engineering team.
The team is responsible for ingestion, processing, and serving bronze level data to other analytic teams in the organization.
In this role, you will define the data architecture of our unified Data Lakehouse, own all ETL and streaming operations, define governance processes and implement tools, make sure our data is fresh, accurate and whole always.
Your Day-to-Day
Menor and lead a team of 4-6 data engineers.
Own sensitive data operations, including monitoring, on-call and production operations.
Build and manage all ETL and streaming operations related to the Data Lakehouse.
Develop, maintain, and optimize robust data pipelines and integrations across multiple systems.
Build a platform for other analytic teams to build data products on top of the Data Lakehouse.
Define and implement quality and governance processes to make sure data is fresh, accurate and whole.
Collaborate with engineering, BI, and business teams to translate requirements into scalable data solutions
Work hands-on with data orchestration, transformation, and cloud infrastructure (OCI, Snowflake, AWS)
Support implementation of best practices in data management and observability.

we are looking for a Data Engineer.
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 ore.
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.
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