SSC HR Solutions
via Workable
Senior Data Engineer (Flink)
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 10h 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 22h ago
The date the source published, not the day we noticed it (2026-09-17). Last seen at its source 1h 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 €65k–104k/yr
Middle 50% of 37 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
-
workable employer's own board first seen 10h ago · last seen 1h ago
The listing
Builds and runs real time streaming pipelines, keeping latency low and jobs recoverable at high
volume.
- Strong hands
on Apache Flink across DataStream API and Flink SQL. - Event time processing, checkpointing, savepoints, and state management in
production. - High volume Kafka streaming.
- Data modelling for analytics and streaming into a lakehouse.
- Monitors pipeline health and handles recovery when jobs fail.
Requirements
Requirements
pache Flink
(DataStream, Flink SQL), Kafka, Java, Scala, Python, SQL, Docker, Kubernetes
- Strong hands-on experience with Apache Flink, including DataStream API and Flink SQL.
- Experience with high-volume Kafka streaming and real-time data processing.
- Strong knowledge of event time processing, checkpointing, savepoints, and state management.
- Experience with data modelling for analytics and streaming into a lakehouse.
- Experience monitoring pipeline health and handling job recovery and failures.
- Apache Iceberg or other open table formats.
- Airflow.
- On premises or self managed cluster experience.