
51 - 200 employees
Founded 2006
💼 Consulting
📦 Logistics
🏥 Healthcare
Consulting • Logistics • Healthcare
SSC HR Solutions is a full-service HR consultancy that provides comprehensive human resource solutions tailored to meet the specific talent growth needs of businesses. With operating locations across Egypt, United Arab Emirates, Saudi Arabia, and Bahrain, SSC HR Solutions specializes in employee management, from hiring to termination, ensuring that businesses thrive in a competitive landscape. The company prides itself on understanding client needs and delivering high-quality services that foster growth and partnership.
🕒 September 24
Where this job comes from
Posted on SSC HR Solutions's careers page, not through a job board
First seen by Remote Rocketship September 24
Still open on SSC HR Solutions's site. Checked 2 days ago.

51 - 200 employees
Founded 2006
💼 Consulting
📦 Logistics
🏥 Healthcare
Consulting • Logistics • Healthcare
SSC HR Solutions is a full-service HR consultancy that provides comprehensive human resource solutions tailored to meet the specific talent growth needs of businesses. With operating locations across Egypt, United Arab Emirates, Saudi Arabia, and Bahrain, SSC HR Solutions specializes in employee management, from hiring to termination, ensuring that businesses thrive in a competitive landscape. The company prides itself on understanding client needs and delivering high-quality services that foster growth and partnership.
• Build and run large scale batch data pipelines. • Keep data processing jobs fast and affordable as data volumes grow. • Build and manage large scale Apache Spark data processing jobs. • Perform performance tuning to maintain efficient and reliable pipeline execution. • Support data modelling for analytics. • Organise data in a lakehouse for downstream use. • Handle automated scheduling, monitoring, and data quality checks. • Work with platform and product teams on end to end data flows.
• Strong hands on Apache Spark including performance tuning, not Spark usage through a managed notebook only. • Data modelling for analytics and organising data in a lakehouse so it is usable downstream. • Automated scheduling, monitoring, and data quality checks. • Works with platform and product teams on end to end data flows. • Apache Iceberg or other open table formats. • Trino or similar query engines. • On premises or self managed cluster experience.
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🕒 May 24
L1 Data Engineer building scalable Azure Data Factory and Databricks pipelines. Processing analytics data with Python, PySpark, and SQL.