Production Support Data Engineer

1 week ago

Johannesburg, Gauteng, South Africa Khonology Full time R500 000 - R1 200 000 per year
Khonology is a digital services company focused on software development, Application Support, data analytics and engineering.

We are looking for two Production Support Data Engineers to maintain stability, availability, and performance of the platform and pipelines during the November - January period. The platform enables the cloud-native data ecosystem by providing governed, automated, and scalable data services. Our ecosystems are currently in both Azure and AWS, with work underway to migrate to AWS. The data services provided includes ingestion, processing, cataloging, and analytics. It underpins data products across business units using Databricks, AWS Glue, Redshift, EMR, S3, and Lake Formation, with embedded security, compliance, and FinOps controls.

Key Responsibilities

• Provide operational support for data pipelines, ingestion jobs, and ETL workloads across CIB for Glue, Databricks, Lakeformation, and S3.

• Manage and triage service requests, incident queues, and change controls within ITSM workflows.

• Maintain operational dashboards and Grafana/CloudWatch alerts, ensuring uptime and SLO compliance.

• Perform incident management, RCA, and recovery for data services and integrations.

• Validate daily and weekly data backups, ensuring data-integrity and retention compliance.

• Collaborate with data engineers to deploy, optimize, and troubleshoot ETL code, schemas, and metadata catalogues.

• Maintain operational documentation, dashboards, and Data Factory runbooks.

• Support FinOps and Well-Architected Framework compliance by monitoring resource utilisation and cost efficiency.

• Automate routine operational checks and pipeline monitoring scripts where possible.

Required Skills & Experience

• 3-5 years' experience in data-platform or production-support roles.

• Strong proficiency with AWS Glue, Databricks, S3, IAM, and CloudWatch.

• Familiarity with, Python, and SQL.

• Experience in data-pipeline monitoring, ETL troubleshooting, and data quality validation.

• Knowledge of AWS Lake Formation, EMR, and Athena is advantageous.

• Understanding of data-governance and compliance in regulated financial environments.

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