לוח משרות דרושים מהנדס/ת דאטה/DATA ENGINEER משרה מלאה

Were looking for a highly organized, detail-oriented Open Innovation Coordinator to join our Technology Planning team. This entry-level role is ideal for candidates with strong analytical skills, clear communication, and a background in software-hardware co-design or computer architecture research. Youll support the Technology Planning Manager and team by analyzing technical trends and helping identify new technologies and collaboration opportunities to advance our innovation strategy.
Key Responsibilities:
Conduct deep-tech research, reviews and analyse on emerging technologies using academic, market, and industry sources.
Track developments in areas such as AI infrastructure, AI Data Movement and other related areas.
Synthesize findings into clear, concise internal summaries and presentations.
Support project coordination: timelines, deliverables, and cross-team communication.
Prepare for and participate in international meetings, including collaboration with China-based and European teams.
Manage logistical and administrative tasks for innovation team.

We're looking for a Senior Backend Engineer to join the Acquisition team, as part of the Data Group.
In this role, youll play a key part in designing, developing, and maintaining our data gateway, integrating new data sources into our system, and tackling challenges related to scale, efficiency, and cost-effectiveness. Youll also help research and define solutions to complex technical problems as we continues to innovate in the SaaS security space.
Tech stack: AWS, Kubernetes, Python, Postgres, Redis, Rabbit, Kafka, Date-Lake.

At Ilyon, we build mobile games enjoyed by millions of players around the world. Our decisions are driven by data — from feature development and live ops to user acquisition and monetization. We’re looking for a skilled Data Engineer to help us take our analytics and data infrastructure to the next level. As a Data Engineer, you’ll design and maintain the systems that power insights across the company. You’ll work closely with data analysts, UA managers, and product teams to ensure clean, fast, and scalable access to our most important asset: data. Data Pipeline Development
* Design, build, and maintain scalable, robust ETL/ELT pipelines.
* Ingest data from various sources (APIs, databases, flat files, cloud buckets).
* Automate workflows for batch and/or streaming pipelines (e.g., using Airflow, GCP services).
* Design and organize data for analytics teams in cloud warehouses (BigQuery, Snowflake).
* Implement best practices for partitioning, clustering, and materialized views.
* Manage and optimize data infrastructure (cloud resources, storage, compute).
* Ensure scalability, security, and compliance in data platforms. Data Quality & Governance
* Monitor data integrity, consistency, and accuracy.
* Implement validation, monitoring, and alerting for pipeline health and data accuracy.
* Maintain documentation and data catalogs.
* Troubleshoot failures or performance bottlenecks. Collaboration & Enablement
* Work closely with data analysts, managers, and developers.
* Translate business requirements into technical solutions.
* Support self-service analytics and create reusable datasets.

In your role as a Data Engineer, you'll be actively engaged in the most fascinating and demanding projects for our clients. Handling high-scale operations, heavy traffic, stringent SLAs, and massive data volumes is just the starting point. Our leadership in the realms of Big Data, Streaming Data, and Complex Event Processing (CEP) stems from our adept use of cutting-edge, optimal technologies.
Responsibilities:
Apply software-engineering methods and best practices (Medallion Architecture) in Data Lake management, using tools like DBT.
Develop Data pipelines to ingest and transform data.
Manage and enhance orchestrated pipelines across company
Data Modeling: Developing data models to ensure efficient storage, retrieval, and processing of data, often involving schema design for NoSQL databases, data lakes, and data warehouses. This will also include catalogs of data.
Scalability: Ensuring that the big data architecture can scale horizontally to handle large volumes of data and high traffic loads.
Data Security: Implementing security measures to protect sensitive data, including encryption, access controls, and data masking.
Data Governance: Establishing data governance policies to ensure data quality, compliance with regulations, and data lineage.