לוח משרות דרושים איש ביג דאטה Big Data משרה מלאה

we are expanding, seeking an experienced BI developer for challenging work in the world of Big Data.
Design, develop & maintain the BIG DATA platform (Vertica).
Design, develop & maintain the BIG DATA infrastructure (development, monitoring, installation, integration, etc)
Be part of the dynamic and agile core DBA team.
Collaborate with field engineers for the deployment phases.
Work on major, challenging projects with enterprise and startup customers.
Job location - Herzliya, Israel.

We are looking for an experienced data Engineering team leader In this role, you will lead and strengthen our data Team, drive innovation, and ensure the robustness of our data and analytics platforms.
A day in the life and how youll make an impact:
* Drive the technical strategy and roadmap for the data engineering function, ensuring alignment with overall business objectives.
* Own the design, development, and evolution of scalable, high-performance data pipelines to enable diverse and growing business needs.
* Establish and enforce a strong data governance framework, including comprehensive data quality standards, monitoring, and security protocols, taking full accountability for data integrity and reliability.
* Lead the continuous enhancement and optimization of the data analytics platform and infrastructure, focusing on performance, scalability, and cost efficiency.
* Champion the complete data lifecycle, from robust infrastructure and data ingestion to detailed analysis and automated reporting, to maximize the strategic value of data and drive business growth.

Our Data team consists of highly skilled senior software and data professionals who collaborate to solve complex data challenges. We process billions of records daily from multiple sources using diverse infra and multi-stage pipelines with intricate data structures and advanced queries, and complex BI.

A bit about our infrastructure. Our main databases are Snowflake, Iceberg on AWS, and Trino. Spark on EMR processes the huge influx of data. Airflow does most of the ETL.

The data we deliver drives insights both for internal and external customers. Our internal customers use it routinely for decision-making across the organization, such enhancing our product offerings.

What Youll Do
Build, maintain, and optimize data infrastructure.
Contribute to the evolution of our AWS-based infrastructure.
Work with database technologies - Snowflake, Iceberg, Trino, Athena, and Glue.
Utilize Airflow, Spark, Kubernetes, ArgoCD and AWS.
Provide AI tools to ease data access for our customers.
Integrate external tools such as for anomaly detection or data sources ingestion.
Use AI to accelerate your development.
Assures the quality of the infra by employed QA automation methods.

as a revenue operations manager, you'll be at the heart of aligning our gtm teams by managing processes, operations, and analytics. you'll turn complex datasets into actionable growth strategies, own the integrity of our revenue funnel, streamline workflows through automation, and deliver insights that guide our next steps. your goal is to ensure data clarity and operational efficiency across the entire customer journey-from initial lead to long-term retention.
maintain a "single source of truth" by managing database hygiene, lead routing, and the end-to-end lead-to-cash process
administer the tech stack and design scalable integrations between the CRM and third-party tools like gong and zoominfo/clay, ensuring minimal data friction
identify bottlenecks in the sales funnel through data analysis and implement automated workflows to boost team efficiency
build and maintain dashboards to track north star metrics, providing proactive insights to leadership and gtm teams
deliver weekly reports on pipeline health, sales velocity, and churn trends
drive team adoption of tools, processes, and integrations through data -backed training sessions and documentation
we're a newly acquired part of the company, on a mission to redefine how software is built. our ai-powered platform enables anyone to create custom software applications using natural language-no coding required. operating like a startup within the company, we're fast, collaborative, and focused on solving complex problems with simple, powerful solutions.
we exist to empower creators, solo founders, startups, entrepreneurs, and side hustlers to bring their ideas to life. whether you're launching a product, validating a concept, or exploring a new idea, we are here to help you build it.
we're growing rapidly, the potential is immense, and with your expertise, we can drive user-driven growth to new heights.

We are looking for an experienced Backend Developer with a passion for data to join our big data group.
Job Id: 25074
As a member of the team you will be a part of a fast, highly-scalable and fully managed data platform which handles terabytes of data per day in a cloud environment.
We are looking for an engineer who will work with multiple technologies stack: Kafka (Azure Event Hub), Kubernetes, Function Apps, Azure Data Explorer, MongoDB, etc.
Using several coding languages like Golang, NodeJS (TypeScript), and Python.
We are required to write efficient code that supports large-scale distributed systems.
Key Responsibilities
Design and build new solutions/features to help our customers improve their cloud security.
Gain experience with new technologies and languages, develop challenging solutions, and have a great opportunity to grow and create impact.
Constantly Improve existing implementations.
Adapt and take on more responsibilities and own your share of the product.
Work with product managers, business, and other teams.

we are looking for a Data Engineer to join our growing BI team. This role goes beyond building pipelines. You will help shape our data platform as a shared product - supporting analytics, reporting, and decision-making across key company data domains such as Product, Sales, HR, and others. Your work will directly influence how stakeholders interact with data today and how the platform evolves in the years ahead.

What Youll Be Doing

Architect & Own: Lead the design and development of scalable data warehouse and BI solutions. You will make early-stage architectural decisions and own their long-term impact.
Infrastructure as a Product: Build core data infrastructure and developer experiences that others rely on, ensuring high availability and system reliability.
End-to-End ELT/ETL: Solve complex integration problems by sourcing data from structured and unstructured sources using Rivery, Python, and optimal ETL patterns.
Data Quality & Governance: Implement frameworks for schema evolution, anomaly detection, and data freshness. You will determine security models based on privacy requirements and evolve governance processes.
Strategic Collaboration: Partner with Engineers, Product Managers, and Data Analysts to conceptualize data needs and represent key insights in a meaningful way.
Optimization: Assist in owning production processes, optimizing complex code through advanced algorithmic concepts to manage operational cost-benefit tradeoffs.

As part of our Customers Company Data Engineering team, you will not only build scalable data features and pipelines but also directly enable portfolio growth by supporting new business capabilities in the Credit Card and Servicing business units.

Responsibilities

Design and build data solutions that support Credit Card and Servicing business goals.
Develop advanced data pipelines to support the infrastructure, architecture and the product growth initiatives.
Create ETL/ELT processes and SQL queries to bring data to the data warehouse and other data sources.
Own and evolve data lake pipelines, maintenance, schema management, and improvements.
Collaborate with stakeholders across Product, Backend Engineering, and Data Science to align technical work with business outcomes.
Implement new tools and modern development approaches that improve both scalability and business agility.
Ensure adherence to coding best practices and development of reusable code.
Constantly monitor the data platform and make recommendations to enhance architecture, performance, and cost efficiency.