Tech Lead - Data Engineer

About the Role:
We are seeking a

Quantexa Certified Engineer

to join our Data Engineering and Analytics team.

The ideal candidate will be responsible for configuring, deploying, and maintaining Quantexa software on leading cloud platforms while leveraging their expertise in data engineering languages and frameworks.
Key Responsibilities:
Configure, deploy, and manage

Quantexa software

solutions on

AWS, Azure, or Google Cloud

environments.
Integrate Quantexa with enterprise data sources, ensuring optimal data ingestion and processing.
Collaborate with cross-functional teams to design and implement scalable data pipelines.
Monitor, troubleshoot, and optimize Quantexa deployments for performance and reliability.
Support implementation of entity resolution, data fusion, and network analytics use cases using Quantexa.
Ensure compliance with security and governance standards across cloud environments.
Work closely with data scientists, analysts, and architects to enable advanced analytics and insights.
Required Skills and Qualifications:
Quantexa Certification

(mandatory).
Strong experience configuring and deploying applications on

AWS, Azure, or Google Cloud Platform (GCP) .
Proficiency in

Scala (preferred) ,

Java ,

Python , or other data engineering languages.
Hands-on experience with

data integration, ETL, and pipeline orchestration

tools.
Understanding of

big data frameworks

(Spark, Hadoop, etc.) and

data modeling .
Familiarity with

CI/CD pipelines

and

Infrastructure as Code (IaC)

practices.
Excellent problem-solving, communication, and collaboration skills.
Good to Have:
Experience implementing

Quantexa use cases

(e.g., fraud detection, AML, customer 360).
Exposure to

Kubernetes, Docker , or container-based deployment.
Knowledge of

data governance ,

lineage , and

security best practices .
Education:
Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.