תיאור המשרה
Description
What is our mission?
Our mission is to empower our clients by providing them with cutting-edge technology for a safer world. Our Data Platform Team is at the forefront of this mission, democratizing data with innovative solutions that transform forensic data into actionable investigative insights. We are dedicated to excellence, using modern data architectures within AWS to create a state-of-the-art data lake environment that is both standard-compliant and robust.
What are we looking for?
We are seeking a highly skilled Senior Backend Data Engineer to join our dynamic team. This role offers the chance to make a significant impact by enhancing the performance, scalability, and stability of our data pipelines.
you will be instrumental in pioneering new features and driving the continuous improvement of our production code.
Why Cellebrite?
Joining Cellebrite means collaborating with dedicated professionals on mission-critical technology. We offer a hybrid work environment, with a balance between on-site collaboration in Petah Tikva and the flexibility of remote work. Our culture thrives on innovation, and we value the contribution of every team member. Cellebrite is where you can bring your expertise to solve complex challenges and contribute to a safer world.
What You'll Do?
Design and implement ETL functions to optimize forensic data processing.
Backend development working to implement new API’s and features that will enrich the main data pipeline in Cellebrite Platform product.
Execute PoCs for new data platform features and integrate successful ones.
Enhance the performance and stability of production-level code.
Utilize AWS services , including Step Functions, AWS lambda, SQS, SNS, Event Bridge, AWS Athena, ECS Fargate, AWS Glue, and EMR, to manage data workflows.
Perform basic DevOps tasks including Kubernetes deployments, serverless/ terranform and operate with APM tools to monitor and improve system performance.
What are the requirements?
A total of 7 years of experience in software development.
At least 3 years of proven hands-on data engineering experience on AWS, specifically in ETL related technologies like Spark, Glue, Athena, Step Functions, Parquet.
Proven experience in data cleansing, manipulation and aggregation using python and/or scala.
AWS Data Engineering certification is a plus.
A team player mindset, strong communication skills, and the ability to work independently.
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