Master Works is hiring an experienced Data Engineer (5+ years) in Riyadh to design and optimize large-scale real-time and batch data pipelines within the Telecom domain.
Design, develop, and maintain real-time and batch data pipelines leveraging Kafka, Spark, and Hadoop components.
Must have understanding of Teradata CLDM, should know how to create new Data Model or modify existing data model based on business requirement Collaborate with business analysts and data architects to translate business requirements into robust data models and ETL frameworks.
Apply Relational and Dimensional modeling techniques to design databases and ensure data is organized effectively for both operational and analytical purposes.
Write, debug, and optimize SQL and Stored Procedures to ensure efficient data processing.
Work closely with BI, Data Science, and Campaign teams to ensure seamless data availability for analytics Work closely with Data Architects, Analysts, and Business Stakeholders to translate business requirements into database solutions.
Ensure all database design and code is well-documented and follows best practices for performance and maintainability.
Involves designing fact and dimension tables for reporting and analytics purposes, often in a star or snowflake schema.
Develop and maintain technical documentation (data flow diagrams, source-to-target mappings, architecture documents).
Ensure that the Data Dictionary is always up-to-date, capturing all changes to the database schema, including newly created or modified tables, columns, views, Perform data quality checks, validation, and ensure end-to-end data accuracy and lineage.
Support and troubleshoot real-time streaming jobs and ensure high availability of data pipelines Have-Must Strong expertise in real-time data integration using Kafka, Spark Streaming, or Dataflow.
Hands-on experience with Hadoop ecosystem components (HDFS, Hive, Sqoop, Spark etc.
). Strong Data Modeling concepts including FSLDM, CLDM, and Dimensional / Data Vault modeling.
Deep understanding of Telecom domain (BSS/OSS, CDR, usage, revenue, and campaign data).
Experience building and optimizing ETL pipelines and data ingestion frameworks for structured and unstructured data.
Proficiency in SQL and distributed data processing using Hive, Spark SQL, or PySpark.
Good understanding of data governance, data quality, and lineage frameworks.
Strong analytical and problem-solving skills.
Excellent communication and collaboration skills with cross-functional teams.
Experience in working on data vartulization tools like (Tibco.
Trino etc)   Good-to-Have Familiarity with Data Catalogs, Metadata Management, and NDMO data governance standards.
  Experience with Data Catalogue tools.
Familiarity with CI/CD pipelines, Git.
Knowledge of ETL orchestration tools like Airflow, NiFi