Data Engineer – Banking Domain (Azure & Cloud)

About the role

We are looking for an experienced Data Engineer to design, build, and maintain batch and streaming pipelines for a banking client. The role focuses on ingesting, cleaning, and standardising both structured and unstructured data, feeding AI and analytics platforms while ensuring strict security and governance.

Key responsibilities

• Develop and operate data pipelines on Microsoft Azure (Fabric, Synapse, Data Factory, Databricks) and open‑source tools (Airflow, Spark, Kafka).
• Integrate enterprise systems and unstructured sources such as documents and SharePoint into analytics/AI solutions.
• Maintain vector‑store feeds, data quality, lineage, and metadata for downstream AI copilots.
• Implement classification, tagging, row‑level and document‑level security, encryption, masking, and tokenisation.
• Manage secrets and credentials using Azure Key Vault or similar vault solutions.
• Provide full audit trails and data lineage for compliance reporting.

Required profile

• 4+ years of hands‑on data engineering experience, preferably in the banking or financial services sector.
• Strong SQL and Python programming skills.
• Practical experience with data quality, metadata management, and troubleshooting data synchronization.
• Familiarity with security best practices for PII/PCI data.

Required skills

• Microsoft Fabric, Azure Synapse, Azure Data Factory, Azure Databricks, Azure Data Lake Storage
• Microsoft Purview, Azure AI Search
• Apache Airflow, Apache Spark, Apache Kafka
• dbt, Great Expectations
• PostgreSQL, pgvector
• OpenMetadata, DataHub
• SQL, Python
• Azure Key Vault (or similar secret management)