Senior Data Engineer

About the role

Rakbank is looking for an experienced Lead Data Engineering / Platform Operations professional to own the design, development and operation of its enterprise data platform. The role focuses on building scalable pipelines, managing the Databricks Lakehouse and enabling analytics, AI and regulatory reporting across the bank.

Key responsibilities

• Lead design, development and operation of batch, micro‑batch and real‑time data ingestion pipelines.
• Engineer and manage the Databricks Lakehouse platform, including Delta Lake optimisation, performance tuning and reliability.
• Implement and govern Unity Catalog with security controls, lineage tracking and access management.
• Build and maintain dbt transformation frameworks, testing standards, documentation and CI/CD integration.
• Drive DataOps excellence through automated testing, monitoring, observability and incident management.
• Manage Confluent/Kafka streaming and CDC capabilities for resilient real‑time data movement.
• Partner with AI Platform Engineering to support feature pipelines and AI‑powered data products.
• Own FinOps activities to optimise cloud spend across Databricks, Azure Data Factory, Confluent and storage services.
• Ensure compliance with data security, privacy, governance and regulatory requirements.
• Lead, coach and develop a high‑performing team of Data Engineers.

Required profile

• 10+ years of data engineering experience, including at least 3 years in a technical leadership role.
• Strong hands‑on expertise with Databricks (Delta Lake, Unity Catalog, Workflows, PySpark, Spark SQL).
• Proven experience with Azure Data Factory for enterprise data integration.
• Deep experience with Confluent/Kafka, CDC technologies and event‑driven architectures.
• Knowledge of dbt, automated testing frameworks, DataOps practices and CI/CD pipelines.
• Experience managing platform reliability, data quality, observability and incident response.
• Understanding of cloud cost optimisation, FinOps and platform governance.
• Bachelor’s degree in Computer Science, Data Engineering, IT or related field.
• Relevant certifications (Databricks Certified Data Engineer Professional, Azure Data Engineer) are a plus.

Required skills

• Databricks
• Delta Lake
• Unity Catalog
• Databricks Workflows
• PySpark
• Spark SQL
• Azure Data Factory
• Confluent/Kafka
• CDC technologies
• dbt
• CI/CD pipelines