דרושים » דאטה » Senior Analytics Engineer

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.

We are looking for a brilliant Data Engineer- an independent, logical thinker who enjoys solving complex problems and building scalable data solutions. You will own and evolve the data foundations that power Product, Finance, Operations, and Business teams. Working closely with diverse stakeholders, Analysts, and R&D teams, you will serve as a technical partner, translating complex business challenges into robust data models, pipelines, and infrastructure. You should be able to translate business and data requirements into scalable data pipelines and data models, integrating multiple internal and external data sources using the most appropriate technologies. Beyond building pipelines, you will improve data quality, modernize existing data assets, automate manual workflows, and help create a clean, reliable, and scalable data ecosystem that supports the company's growth.

Roles and Responsibilities:
Design and build end-to-end data pipelines - From defining source structures and integrating APIs to delivering clean, trusted datasets that enable analytics, reporting, and operational workflows.
Translate business needs into scalable data solutions based on business priorities and the product roadmap, understand technical requirements, and deliver purpose-built pipelines and tools.
Act as the technical partner for Product, Finance, Operations, and R&D teams, translating business needs into scalable data models, pipelines, and internal tools while ensuring reliable, trusted data across the organization.
Write high-quality, maintainable code, while following best practices and leveraging modern data tooling and CI/CD principles.
Drive data quality and reliability - Monitor, validate, troubleshoot, and continuously improve data quality and pipeline reliability across the data platform.

Required AI Data Engineer
About the role:
We're building the intelligence layer that lets everyone ask hard questions of our data and get trustworthy answers - in plain language, in seconds. As AI Data Engineer, you own the semantic and AI-native surface of our Snowflake platform: the governed semantic layer that defines "what a metric means," the Cortex Agents that let business users query it conversationally, and the infrastructure that keeps all of it fast, reliable, and ready to scale.
This is a builder-owner role. You'll ship the semantic models, wire up the agents, and set the standard for how analysts across the company work with data. You'll also lead the Data Analyst guild - the connective tissue that keeps our hub-and-spoke analytics model coherent as it grows.
If you're excited by the space where data engineering, LLM tooling, and analytics governance meet, this role sits right in the middle of it.
What youll Own:
Snowflake semantic layer - Own the semantic layer end-to-end as the single source of truth for metrics; design semantic models, enforce naming standards, and ensure consistent metric definitions across dashboards and AI agents.
Cortex Agents - Design and deploy conversational AI agents using Cortex Analyst and Cortex Search; tune for accuracy and safety, expose through multiple surfaces (Snowflake Intelligence, Streamlit, MCP), and build evaluation harnesses to maintain quality at scale.
Data craft (Analytics guild) - Co-lead the technical track of the Analytics guild; set SQL and modeling standards, run technical enablement and code reviews, and serve as the technical authority for analysts.
Scaling data infrastructure - Improve performance, reliability, cost efficiency, and governance across the dbt/Airflow/Airbyte/Snowflake stack as data volume and query load grow; optimize warehouse sizing, medallion layers, and ingestion pipelines.
What you'll do day to day:
Model and maintain semantic views that power both dashboards and AI agents, keeping definitions versioned, tested, and certified.
Build, evaluate, and iterate on Cortex Agents - including retrieval quality, guardrails, and observability.
Extend and optimize dbt models, Airflow DAGs, and Airbyte connectors across bronze/silver/gold layers.
Partner with GTM, Finance, CS, and Product stakeholders to translate business questions into governed, reusable data assets.
Run the Data Analyst guild: standards, reviews, enablement, and tooling.
Own data quality, lineage, and cost monitoring across the Snowflake platform.
Expose data and agents through Streamlit apps, BI tools (Omni), and MCP servers for internal AI workflows.

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.

abra professional services is seeking a Data Analytics Architect / Principal Data Engineer We are looking for a skilled Data Analytics Architect / Principal Data Engineer to lead the organization’s analytics data domain, design large-scale data architecture, build advanced analytical models, define organizational data modeling standards, and implement innovative AI and LLM-based technologies. This role requires deep expertise in data engineering, analytics, BI, SQL, PostgreSQL, data modeling, performance optimization, data governance, and the integration of AI tools into data engineering processes. A full-time hybrid position based in Central Israel. The first 4–6 months will be based in Tel Aviv, followed by a transition to the Lod area. The position includes 1 day a week remote. Key Responsibilities:
* Design and develop data architecture that supports large-scale analytics and business intelligence.
* Lead the design and implementation of complex data models and enterprise data modeling solutions.
* Define organizational standards, methodologies, and best practices in the data domain.
* Optimize database performance, analytical queries, and reporting processes.
* Lead LLM-based development and implement AI tools within data engineering processes.
* Mentor data engineers, conduct code reviews and architecture reviews.
* Collaborate with management and business stakeholders to build a technological roadmap.
* Establish frameworks for data quality and data governance.
* Lead initiatives to improve the reliability and stability of BI and analytics systems.
* Evaluate new technologies and lead the adoption of innovative solutions across the organization.
* Lead the design and implementation of end-to-end analytics platforms.

As a Senior Data Engineer , you will play a key role in building and scaling the companys data infrastructure. Youll be responsible for creating the foundation that enables teams across the organization to access, analyze, and leverage data effectively. Working closely with Data Science, Delivery, Product, GTM, and Analytics teams, youll design and maintain data pipelines, manage our data warehouse, and transform raw data into structured, reliable assets that power business and product decisions.



What Youll Do

Build and Manage Data Infrastructure: Own and maintain Nomas data warehouse infrastructure, ensuring scalability, reliability, and performance
Develop Data Pipelines: Design, build, and maintain data pipelines that transform company data into structured, queryable assets
Enable Data-Driven Decisions: Partner with Engineering, Data Science, Product and Analytics teams to deliver trusted data foundations and actionable insights.
Create BI Dashboards: Build and maintain dashboards and reporting layers that support product, and operational decision-making
Ensure Data Quality and Accessibility: Implement best practices for data modeling, governance, monitoring, and reliability

We are looking for a Senior Data Platform Engineer to join our growing Platform team and help build the foundation that powers our products, analytics, and data-driven decision making.

In this role, you will design, build, and operate the core data infrastructure that enables engineering teams to move fast while maintaining reliability, scalability, and operational excellence. You will work across databases, streaming systems, data lakes, cloud infrastructure, and platform services, solving complex challenges around scale, performance, and resilience.

As a senior engineer, you will play a key role in shaping our data architecture, driving technical decisions, and mentoring other engineers.

Responsibilities
Design, build, and operate scalable data platform services and infrastructure.
Develop high-quality software for distributed systems and data-intensive applications.
Design and optimize data storage solutions across operational databases, data lakes, and analytical systems.
Drive database performance improvements through query optimization, indexing strategies, schema design, and capacity planning.
Build and maintain event-driven architectures and streaming data pipelines.
Develop and improve data ingestion, transformation, orchestration, and processing frameworks.
Partner with product, engineering, analytics, and AI teams to deliver scalable and reliable data solutions.
Improve platform reliability, observability, and operational excellence through automation and engineering best practices.
Build and enhance CI/CD pipelines, deployment processes, and developer tooling.
Lead architecture discussions and contribute to long-term platform strategy.
Troubleshoot complex production issues and drive root-cause analysis and preventative improvements.
Mentor engineers through code reviews, technical guidance, and knowledge sharing.

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 .
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 next-generation data stack.
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 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

As a Data Analyst, you'll play a key role in shaping product strategy and business decisions by turning complex data into actionable insights. You'll partner with Product, Engineering, and customer-facing teams to build scalable analytics solutions, define success metrics, and uncover opportunities that drive impact across our platform

What youll do:

Own the analytics domain for key products and strategic initiatives.
Analyze large-scale operational and product datasets to identify trends, opportunities, and business insights.
Design, build, and maintain dashboards and reporting solutions using modern BI tools.
Develop automated data pipelines and analytical workflows using Python and Airflow.
Partner closely with Product Managers to define KPIs, measure success, and support product decision-making.
Work with customer-facing teams to provide insights and occasionally participate in customer discussions and presentations.
Build internal tools and processes that improve data accessibility and operational efficiency.
Utilize modern AI-assisted development tools (such as Claude Code) to accelerate analysis, automation, and development workflows.
Translate complex data findings into clear recommendations for both technical and non-technical stakeholders.

Were looking for a BI & Data Engineering Team Lead to join our BI team and take end-to-end ownership of high-impact analytics foundations while mentoring a team of 4-6 talented BI Data Engineers. This role sits at the core of how measures success, makes decisions, and scales-turning raw data into trusted, business-critical insights used across Product, GTM, and Finance.

In this role, you'll combine people leadership with hands-on technical depth (roughly 30% of your time), owning the roadmap, architecture, and delivery of BI platform. Youll shape how AI and agentic workflows transform the way BI is built and consumed, helping 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 while leading and growing people
You like turning ambiguous business questions into clear, governed metrics and scalable data models
You care about data quality, performance, and trust at scale, as well as optimization and FinOps practices
You enjoy mentoring, setting technical standards, and leading by example with a hands-on approach (~30%)
You actively leverage AI tools and agentic automations to improve development speed, analytical accuracy, and metric governance