Senior Data Engineer (Spark)
SSC HR Solutions Open · verified Oct 24, 2026 At a glance
Senior Data Engineering role at SSC HR Solutions. Remote, Egypt.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and operate batch pipelines, keeping processing efficient and costs controlled as data grows
- Tune Spark jobs to improve speed and keep pipeline runs reliable
- Shape analytical models and organise lakehouse data for downstream use
- Set up scheduling, monitoring and quality checks, and coordinate end-to-end data flows with platform and product teams
What you bring
- Strong practical Apache Spark experience, including tuning jobs rather than using Spark only through managed notebooks
- Experience modelling analytics data and structuring it in a lakehouse for downstream use
- Hands-on work with automated scheduling, monitoring and data quality checks
- Familiarity with Apache Iceberg or another open table format, Trino or a comparable query engine, and self-managed clusters
Who this fits
This senior role suits a data engineer who has built and tuned Spark pipelines and worked across lakehouse modelling and operations. The position is based in Cairo and remote.
From the employer
Description
Builds and runs large scale batch data pipelines, keeping jobs fast and affordable as data volumes grow. Works with Apache Spark to build and manage large scale data processing jobs, including performance tuning to maintain efficient and reliable pipeline execution. Supports data modelling for analytics and organises data in a lakehouse so it is usable downstream. Handles automated scheduling, monitoring, and data quality checks, while working with platform and product teams on end to end data flows.
Requirements
Requirements
- 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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