דרושים » תוכנה » Data Engineer

We are looking for a Data Engineer to join our growing team!
In this role, you will be responsible for:
Designing, building, and maintaining scalable data pipeline architectures
Developing ETL processes to integrate data from multiple sources
Creating and optimizing data models for efficient storage and retrieval
Implementing data quality controls and monitoring systems
Collaborating with data scientists and analysts to deliver data solutions
Building and maintaining data warehouses and data lakes
Performing in-depth data analysis and providing insights to stakeholders
Taking full ownership of data quality, documentation, and governance processes
Building and maintaining comprehensive reports and dashboards
Ensuring data security and regulatory compliance.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply best practices for data security, integrity, and performance across all systems.

We are seeking a skilled Data/ Backend Engineer to design and implement complex, high-scale systems that retrieve, process, and analyze data from the digital world. This role involves developing and maintaining backend infrastructure, creating robust data pipelines, and ensuring the seamless operation of data-driven products and services.
Key Responsibilities:
- Design and build high-scale systems and services to support data infrastructure and production systems.
- Develop and maintain data processing pipelines using technologies such as PySpark, Hadoop, and Databricks.
- Implement dockerized high-performance microservices and manage their deployment.
- Monitor and debug backend systems and data pipelines to identify and resolve bottlenecks and failures.
- Work collaboratively with data scientists, analysts, and other engineers to develop and maintain data-driven solutions.
- Ensure data is ingested correctly from various sources and is processed efficiently.

We are looking for a Data Engineer to join our team and help advance our Apps solution. Our product is designed to provide detailed and accurate insights into Apps Analytics, such as traffic estimation, revenue analysis, and app characterization. The role involves constructing and maintaining scalable data pipelines, developing and integrating machine learning models, and ensuring data integrity and efficiency. You will work closely with a diverse team of scientists, engineers, analysts, and collaborate with business and product stakeholders.
Key Responsibilities:
Develop and implement complex, innovative big data ML algorithms for new features, working in collaboration with data scientists and analysts.
Optimize and maintain end-to-end data pipelines using big data technologies to ensure efficiency and performance.
Monitor data pipelines to ensure data integrity and promptly troubleshoot any issues that arise.

At our company, were reinventing DevOps and MLOps to help the worlds greatest companies innovate -- and we want you along for the ride. This is a special place with a unique combination of brilliance, spirit and just all-around great people. Here, if youre willing to do more, your career can take off. And since software plays a central role in everyones lives, youll be part of an important mission. Thousands of customers, including the majority of the Fortune 100, trust our company to manage, accelerate, and secure their software delivery from code to production - a concept we call liquid software. Wouldn't it be amazing if you could join us in our journey?
About the Team
We are seeking a highly skilled Senior Data Engineer to join our company's ML Data Group and help drive the development and optimization of our cutting-edge data infrastructure. As a key member of the company's ML Platform team, you will play an instrumental role in building and evolving our feature store data pipeline, enabling machine learning teams to efficiently access and work with high-quality, real-time data at scale.
In this dynamic, fast-paced environment, you will collaborate with other data professionals to create robust, scalable data solutions. You will be responsible for architecting, designing, and implementing data pipelines that ensure reliable data ingestion, transformation, and storage, ultimately supporting the production of high-performance ML models.
We are looking for data-driven problem-solvers who thrive in ambiguous, fast-moving environments and are passionate about building data systems that empower teams to innovate and scale. We value independent thinkers with a strong sense of ownership, who can take challenges from concept to production while continuously improving our data infrastructure.
As a Data Engineer at our company's ML you will...
Design and implement large-scale batch & streaming data pipelines infrastructure
Build and optimize data workflows for maximum reliability and performance
Develop solutions for real-time data processing and analytics
Implement data consistency checks and quality assurance processes
Design and maintain state management systems for distributed data processing
Take a crucial role in building the group's engineering culture, tools, and methodologies
Define abstractions, methodologies, and coding standards for the entire Data Engineering pipeline.

We're seeking talented data engineers to join our rapidly growing team, which includes senior software and data engineers. Together, we drive our data platform from acquisition and processing to enrichment, delivering valuable business insights. Join us in designing and maintaining robust data pipelines, making an impact in our collaborative and innovative workplace.

Responsibilities
Design, implement, and optimize scalable data pipelines for efficient processing and analysis.
Build and maintain robust data acquisition systems to collect, process, and store data from diverse sources.
Take part in developing agentic capabilities.
Mentor, support, and guide junior team members, sharing expertise and fostering their professional development.
Collaborate with DevOps, Data Science, and Product teams to understand needs and deliver tailored data solutions.
Monitor data pipelines and production environments proactively to detect and resolve issues promptly.
Apply and be responsible for best practices in data security, integrity, and performance across all systems.

we are looking for a BI Data Engineer
As a BI Data Engineer , you will play a key role in designing, developing, and maintaining scalable data solutions that generate business impact.

Key Responsibilities:

Design and implement robust data models, ETL pipelines, and data flows that support advanced analytics and reporting across the organization.
Develop new data solutions from scratch while maintaining and enhancing existing infrastructure
Partner with the Data Architect to manage and evolve Skais data architecture, ensuring it accurately reflects and supports the evolving business model.
Work closely with business stakeholders to convert complex requirements into actionable data insights that drive informed decisions.
Become a focal point for all data-related matters in the organization.

We are looking for our first dedicated Data Engineer a self-motivated and proactive professional with a strong can-do attitude and a sense of ownership. This role involves taking responsibility across all data domains within the company, working closely with our analytics and development teams to build and maintain the data infrastructure that supports business needs. This position is ideal for someone ready to independently lead data engineering efforts and make a meaningful impact.

Responsibilities:
Design, develop, and maintain scalable data pipelines and ETL workflows using tools such as Python, dbt, and Airflow.
Architect and optimize our data warehouse to support efficient analytics, reporting, and business intelligence at scale.
Model and structure data from multiple internal and external sources (such as Salesforce, Jira, Mixpanel, etc.) into clean, reliable, and analytics-ready datasets.
Collaborate closely with our systems architect, analytics, and development teams to translate business requirements into robust and efficient technical data solutions.
Monitor and optimize pipeline performance to ensure data completeness and scalability.
Serve as a key partner and subject-matter expert on all data-related topics within the team.
Implement data quality checks, anomaly detection and validation processes to ensure data reliability.

Join our Partners Data Team as a Senior Data Engineer and take on the challenge of designing, implementing, and maintaining critical data pipelines. You'll play a key role in ensuring data integrity and accessibility, enabling our teams to drive strategy and optimize partner experiences.
In your day-to-day, you will:
Design and implement data pipelines, ensuring the seamless flow of information into our data warehouse.
Develop scalable solutions to address data gaps and process design needs.
Monitor data pipeline performance, troubleshoot issues, and guarantee data infrastructure availability.
Collaborate with analysts and product managers to align data models with business priorities.
Engage with a diverse group of stakeholders, including data engineers, analysts, and data scientists, to support data-driven decision-making.

As a Big Data & GenAI Engineering Lead within our company's Data & AI Department, you will play a pivotal role in building the data and AI backbone that empowers product innovation and intelligent business decisions. You will lead the design and implementation of our companys next-generation lakehouse architecture, real-time data infrastructure, and GenAI-enriched solutions, helping drive automation, insights, and personalization at scale. In this role, you will architect and optimize our modern data platform while also integrating and operationalizing Generative AI models to support go-to-market use cases. This includes embedding LLMs and vector search into core data workflows, establishing secure and scalable RAG pipelines, and partnering cross-functionally to deliver impactful AI applications.
As a Big Data & GenAI Engineering Lead in our company you will...
Design, lead, and evolve our companys petabyte-scale Lakehouse and modern data platform to meet performance, scalability, privacy, and extensibility goals.
Architect and implement GenAI-powered data solutions, including retrieval-augmented generation (RAG), semantic search, and LLM orchestration frameworks tailored to business and developer use cases.
Partner with product, engineering, and business stakeholders to identify and develop AI-first use cases, such as intelligent assistants, code insights, anomaly detection, and generative reporting.
Integrate open-source and commercial LLMs securely into data products using frameworks such as LangChain, or similar, to augment AI capabilities into data products.
Collaborate closely with engineering teams to drive instrumentation, telemetry capture, and high-quality data pipelines that feed both analytics and GenAI applications.
Provide technical leadership and mentorship to a cross-functional team of data and ML engineers, ensuring adherence to best practices in data and AI engineering.
Lead tool evaluation, architectural PoCs, and decisions on foundational AI/ML tooling (e.g., vector databases, feature stores, orchestration platforms).
Foster platform adoption through enablement resources, shared assets, and developer-facing APIs and SDKs for accessing GenAI capabilities.