Data Engineer - Experis

#WEAREHIRING Data Engineer
Location: Petah Tikva, Israel

We are looking to expand our Data Engineering capabilities within the Fraud Prevention domain.

In this role, you will work closely with analysts, data scientists, software developers, and product stakeholders to build and maintain scalable data solutions that support analytics, research, and fraud prevention initiatives.

You will take end-to-end ownership of data assets and pipelines, translating complex business and product needs into reliable, scalable data solutions.

What You’ll Do

Gather data needs from internal customers like product and analysts, and translate those requirements into a working database and analytic software.
Develop data-centric software using leading-edge big data technologies. These include database design, batch, and real-time ETL pipelines.
End to end ownership of teams data assets including: data quality, operational ownership, on-call (during working hours).
Collaborate with colleagues both locally and in remote locations.
Influence the software architecture and working procedures for building data and analytics solutions.
Participate in design and code reviews.
Independent and communicative, team player mind set – manage your own time, and work both independently and as part of a team.
Be the go-to person for anything and everything regarding understanding the data exploration, pipelines, analytics, etc.

Metrics / Measurement

Have an impact on satisfying customers and reducing financial fraud.
Contribute to experiments and research on how to enhance our capabilities.

Minimum Requirements

SQL, Spark, Entity Relationship Data Modeling, Python, Shell scripting.
Information Systems, Industrial Engineering, or Computer Science degree, or relevant work experience (army tech units and similar).
Strong business understanding – able to understand complex product flows, understand business pain points, and translate those into data solutions.
Experience dealing directly with internal customers regarding their data needs.
Expert in SQL in a large-scale Data Warehouse, Data Lake, or Lakehouse environment such as Spark, Databricks, Presto/Athena/Trino/Redshift.
Experience developing ETLs / data pipelines end-to-end, including monitoring and orchestration.
Experience working in a cloud environment, preferably AWS, using tools such as EMR/Spark, S3, and EC2.
Experience with logging and monitoring tools such as Splunk, Grafana, etc.
Strong knowledge of database / dimensional modeling / data integration tools.
Experience writing scripts with languages such as Python and Shell scripts in a Linux environment.
High level of English and Hebrew.
AI experience with Agentic development environments (Claude / Cursor, etc.).

Bonus Points

Experience with fraud/cyber systems.
Agentic workflows development for data – such as skills, plugins, agents, etc.
Some knowledge of Data Science / Machine Learning.
Experience with NoSQL databases such as DynamoDB and Cassandra.
Knowledge / experience with Scala and Java.
Some experience with stream processing or near real-time data ingestion.
Some knowledge of graph databases.

Education

Bachelor’s degree in Computer Science or Industrial Engineering.