Data Engineer

About the role

We are seeking a highly skilled and motivated Data Engineer with 5–7 years of experience to design, build, and optimise scalable data pipelines and platforms. The role focuses on banking domain processes, regulatory considerations and enabling data‑driven decision‑making across critical banking functions.

Key responsibilities

• Design, develop and maintain robust, scalable data pipelines using Azure Data Factory and Databricks.
• Implement batch and real‑time data ingestion frameworks leveraging Confluent Kafka.
• Build and optimise data models, transformations and ETL/ELT pipelines with SQL and Spark.
• Develop and manage data storage solutions in Azure Data Lake Storage.
• Ensure high data quality, integrity and governance standards.
• Support data integration across core banking, CRM and other systems.
• Optimise performance of large‑scale datasets and reduce data latency.
• Collaborate with stakeholders to translate requirements into solutions and ensure compliance with banking regulations.

Required profile

• Bachelor’s or Master’s degree in a relevant field.
• Strong analytical, problem‑solving and communication skills.
• Ability to work in fast‑paced environments and collaborate with cross‑functional teams.
• Experience in banking or financial services (preferred).
• Understanding of core banking systems and regulatory frameworks such as KYC and AML.

Required skills

• SQL (complex queries, tuning, modelling).
• Databricks, Spark and PySpark.
• Confluent Kafka and event‑driven architecture.
• Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS).
• CI/CD and DevOps for data platforms.
• Python or Scala.
• Power BI.
• APIs and microservices.
• Data warehousing concepts.