Summary
RAKBANK is seeking a Data Engineer to join its Data & Analytics team in Dubai, within the Information Technology division. The role involves building and maintaining data pipelines and curated datasets on Databricks, supporting analytics, regulatory reporting and AI initiatives. The engineer will implement data quality controls, troubleshoot production issues, support platform migration and collaborate with technical and business teams. Applicants should have 3–7 years of relevant experience and hands-on skills in SQL, Python, PySpark and Databricks.
The posting
As published on rakbank.ae. Pulled from the employer's site and shown as they wrote it.
At Rakbank, we're transforming the way data drives decision-making across the organization. We are looking for a talented Data Engineer to join our growing Data & Analytics team and help build scalable, reliable, and secure data solutions that power analytics, reporting, regulatory, operational, and AI-driven initiatives. The role is based within our Information Technology division and reports to the Lead Data Engineer.
What You Will Do
- Design, build, deploy, and maintain scalable data pipelines on the Databricks Lakehouse platform.
- Develop and optimize data ingestion, transformation, and enrichment processes across batch, streaming, and near-real-time workloads.
- Build and maintain curated datasets and data models that support business intelligence, analytics, regulatory reporting, and AI use cases.
- Implement data quality controls, monitoring, reconciliations, and automated testing frameworks.
- Support migration of legacy data solutions into modern cloud-based data platforms.
- Troubleshoot production issues, perform root-cause analysis, and continuously improve platform reliability.
- Collaborate with architects, analysts, governance teams, and business stakeholders to deliver trusted data products.
Contribute to Agile delivery practices using Azure DevOps, CI/CD, and engineering best practices.
What You Will Bring
- 3-7 years of experience in Data Engineering, Analytics Engineering, Software Engineering, or a related field.
- Strong hands-on experience with SQL, Python, PySpark, and Spark SQL.
- Experience working with Databricks, Delta Lake, Databricks Workflows, and Databricks SQL.
- Knowledge of Azure Data Factory (ADF), dbt, CDC frameworks, and streaming technologies such as Kafka/Confluent.
- Understanding of dimensional modelling, medallion architecture, data quality frameworks, and data governance principles.
- Familiarity with Git, CI/CD practices, and Agile delivery methodologies.
- Strong problem-solving, collaboration, and communication skills.
- Banking or financial services experience is advantageous.
- Azure or Databricks certifications will be an added advantage.