Senior Data Engineer (Spark)
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 1d ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 9d ago
The date the source published, not the day we noticed it (2026-09-23). Last seen at its source 3h ago.
We have tracked this listing since 23 Sep 2026 (9 days). The employer's own board has carried it every time we have read it, most recently 3 hours ago.
Is it remote?
Marked remote on the employer's board
Their board carries a remote setting on this posting — a field they filled in, not wording we read. The location field names somewhere specific, which is usually where the team or the entity sits.
Who may apply?
Egypt
The description states no restriction of its own. This is the source's own tag.
Pay not stated
Similar roles pay €70.6k–104k/yr
Middle 50% of 46 listings that do state pay — Engineering · Senior · EMEA · EUR/year. This employer has published no salary; this is what comparable listings we hold disclose, never converted between currencies or periods. How this is calculated.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
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workable employer's own board first seen 9d ago · last seen 3h ago
The listing
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.