Senior Specialist Data Engineering
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Key skills for this role
About the Role
Ooredoo seeks a Senior Data Engineering Specialist to design and operate scalable data pipelines on GCP. You will build data products for analytics and AI/ML workloads, integrating on-premises sources.
Key Skills for This Role
Responsibilities
- Engineer the data foundation that powers Ooredoo's AI and digital transformation agenda
- Design, build, and operate scalable, governed data pipelines and data products on Ooredoo's Google Cloud Platform (GCP) data platform
- Translate business and analytical needs into production ready, reusable data products that serve analytics, reporting, and AI/ML workloads
- Ensure on premises sources (Teradata, Informatica, Qlik) are reliably integrated and progressively migrated to GCP
Requirements
- 10 years' experience in a similar role
- Prior experience in data engineering, ETL development, and enterprise data warehousing
- Strong hands on GCP data engineering — BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Cloud Storage — with dbt (or equivalent) 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
Full Job Posting
About Us
- Ooredoo is a dynamic global Telecommunications player operating in 10 countries serving more than 138 million customers.
- Ooredoo Qatar employs approximately 1,600 people driving Ooredoo to be the number one choice for world class communications services in Qatar.
About the Business Unit
- Ooredoo places strong emphasis on a data driven culture.
- The AI Hub division is responsible for putting in place and executing the data & AI roadmap, business plan, and strategy.
- Ooredoo is building cloud platform based solutions that host the data platform and support analytics, ML and Gen AI/agentic use cases.
About the Role
- This role is engineering the data foundation that powers Ooredoo's AI and digital transformation agenda.
- The Senior Specialist, Data Engineering designs, builds, and operates scalable, governed data pipelines and data products on Ooredoo's Google Cloud Platform (GCP) data platform.
- Works alongside the data platform delivery partner, data science, and commercial teams to translate business and analytical needs into production ready, reusable data products.
- Ensures on premises sources (Teradata, Informatica, Qlik) are reliably integrated and progressively migrated to GCP.
About You
- 10 years' experience in a similar role.
- Prior experience in data engineering, ETL development, and enterprise data warehousing.
- Strong hands on GCP data engineering — BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Cloud Storage — with dbt (or equivalent) 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.
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