Senior Data Engineer
At Cognyte, you’ll collaborate with expert colleagues around the globe to solve problems most people will never even know exist!
You’ll be part of building unique solutions shaped by real investigative methodologies, enabling our customers to identify, investigate, visualize and prevent criminal, terror and security threats worldwide.
These solutions are used by law enforcement, national security, and national and military intelligence agencies in almost 100 countries to turn massive, diverse data into clear, actionable intelligence for a safer world.
We are looking for a passionate Senior Data Engineer to join our Data Platform team. In this role, you will be an individual contributor working on the design and implementation of our data lakehouse infrastructure. You will help build scalable, high-performance data foundations that support analytics, BI, and future data-driven capabilities across the platform.
The mission is to deliver a successfully working data lakehouse based on modern data engineering technologies, medallion architecture, scalable processing, and reliable data quality.
As a Cognyter you will:
- Design, build, and optimize scalable data lakehouse platforms using technologies such as Spark, Iceberg, Trino, ClickHouse, and AWS/hybrid infrastructure.
- Develop and maintain batch and streaming data pipelines, workflow orchestration, and data-serving layers, ensuring reliability, scalability, and performance.
- Own data modelling, medallion architecture (bronze, silver, gold), ClickHouse optimization, cost estimation, and platform governance, including data quality, lineage, and observability.
- Collaborate with BI users, engineers, and stakeholders to deliver curated datasets, support analytics and reporting, and contribute to architectural decisions.
- Provide hands-on support for platform operations, infrastructure-related tasks, and continuous improvement of the data ecosystem.
Requirements
For that mission you’ll need:
- At least 5 years of total software/data engineering experience.
- Previous experience in a senior-level engineering role.
- Strong hands-on experience with SQL and Python.
- Strong experience with Apache Spark.
- Experience working with large-scale distributed systems and high-volume data.
- Experience with Kubernetes.
- Good English communication skills.
Advantage:
- Experience with Apache Iceberg.
- Experience with data governance, access control, and data security.