Data Integration Expert

This job requires relocation to Saudi Arabia for 12 months. We are seeking a

Data Integration Expert

to architect and implement scalable, secure, and robust data platform solutions to support machine learning (ML), business intelligence (BI), and customer value management (CVM) analytics. This role requires deep expertise in data ingestion, ETL pipelines, and on-premise data platforms like

Cloudera

or

Teradata . Key Responsibilities :

Define and implement

scalable architecture

for data platforms with a focus on

AI and analytics enablement . Ensure the platform supports

end-to-end ML pipelines ,

BI dashboards , and

CVM analytics . Design and maintain

reference models

for data ingestion, transformation, processing, and access. Integrate

security, governance , and

compliance frameworks

(including

PDPL

and other local regulatory standards). Work closely with

data scientists, analysts , and

IT infrastructure teams

to align architecture with business goals. Manage and optimize

ETL pipelines

and ensure

data quality, lineage, and metadata management . Provide hands-on leadership in setting up, maintaining, and evolving

on-premise platforms

such as Cloudera or Teradata. Required Skills :

6–8 years of experience in

building ETL pipelines ,

data integration , and

data platform management . Strong understanding of

on-premise data ecosystems , preferably

Cloudera (Hadoop)

or

Teradata . Proficiency in

data ingestion frameworks ,

data lakes , and

batch + real-time data processing . Experience in

data governance, compliance , and

security standards , especially

PDPL

or similar data privacy laws. Strong knowledge of

SQL, Spark, Hive , and

scripting languages

(e.g., Python, Bash). Ability to collaborate across cross-functional teams and work independently in a fast-paced environment. Preferred Qualifications :

Experience working in

telecom or large-scale enterprise data environments . Familiarity with

Kafka, NiFi , and

data orchestration tools

like

Airflow . Knowledge of

DevOps practices ,

CI / CD pipelines , and

containerization (Docker / Kubernetes)

is a plus.

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