Data Platform Engineer — AI & Analytics

Ooredoo Qatar; Doha; On-site; QAR 420,000 - 640,000; Full time

Job summary

Ooredoo Qatar seeks a Senior Specialist, Data Engineering to architect and operate scalable, governed pipelines on the GCP data platform. You will translate business needs into production-ready data products supporting analytics, AI/ML workloads, and dashboards while integrating on‑prem sources during cloud migrations.

You will collaborate with data science, commercial and infrastructure teams to ensure data quality, governance, and efficient data delivery across CVM, marketing, digital sales

Qualifications

• Bachelor’s Degree in Computer Science, Engineering or Similar.
• 10 years of experience in a similar role.
• Strong hands-on GCP data engineering — BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Cloud Storage for SQL transformation, testing, and lineage.
• Expertise in Informatica for ETL/ELT workflow design, automation, and data quality.
• Deep understanding of building analytical data stores, feature stores, and curated datasets used by data scientists and analysts.
• Strong command of advanced SQL (window functions, aggregations, complex transformations) and Python for data engineering.
• Experience designing curated, and consumption layers and feature stores, with sound data-modelling skills (dimensional modelling, star schema, third normal form).
• Experience supporting BI/reporting platforms such as SAP BusinessObjects, and QlikSense, including data modeling for consumption layers.
• Experience supporting BI and consumption platforms e.g, Looker (preferred), SAP BusinessObjects, and QlikSense — including data modelling for consumption layers.
• Understanding of data governance, metadata management, lineage, data quality, privacy, and security principles.
• Awareness of feature stores, vector stores, and data pipelines that support AI/ML and GenAI (e.g., RAG) use cases is an advantage.
• Strong communication and stakeholder-management skills, with the ability to explain technical concepts in business-friendly language

Responsibilities

• Develop and optimize real time analytical data stores and feature stores to enable data scientists to efficiently train, validate, and deploy models in DataIKU.
• Build robust data ingestion, transformation, and enrichment processes built on real time data products using ETL tools e.g. Informatica.
• Collaborate with data scientists to translate analytical and modeling needs into production ready data assets, features, and reusable data frameworks.
• Ensure seamless integration of datasets with reporting and BI platforms, including SAP BusinessObjects and QlikSense, providing curated, trusted datasets.
• Implement data quality rules, metadata management, and validation frameworks to ensure reliability and governance of mission critical datasets.
• Automate repeated data processes, pipelines, and monitoring systems to minimize manual intervention and improve efficiency.
• Support data platform optimization through performance tuning, workload management, and efficient use of enterprise DWH capabilities.
• Document end to end data flows, data models, pipeline dependencies, and operational processes in alignment with governance best practices.
• Partner with Technology and Infrastructure teams to ensure secure, compliant, and scalable deployment of data engineering solutions.
• Work within a shared function to support commercial growth, cost optimization, customer experience enhancements, and digital transformation initiatives.

Skills

GCP

BigQuery

Dataflow

Dataproc

Pub/Sub

Cloud Composer

SQL

Python

ETL

Data Warehousing

Informatica

Data Modeling

Looker

Data Governance

Education

Bachelor’s Degree in Computer Science, Engineering or Similar

Tools

Informatica

DataIKU

SAP BusinessObjects

QlikSense

Looker

Job description

Ooredoo Qatar seeks a Senior Specialist, Data Engineering to architect and operate scalable, governed pipelines on the GCP data platform. You will translate business needs into production-ready data products supporting analytics, AI/ML workloads, and dashboards while integrating on‑prem sources during cloud migrations.

You will collaborate with data science, commercial and infrastructure teams to ensure data quality, governance, and efficient data delivery across CVM, marketing, digital sales