Azure Data Engineer

Technology Stack : Azure Data Factory, ADLS Gen2, Azure Synapse, Azure Databricks, SQL / PySpark, Azure DevOps, Azure Monitor, Azure Key VaultDomain: Banking - Understanding of banking-specific data models About the RoleWe are seeking a motivated and technically strong Data Engineer to join our Data Platform team, with a primary focus on building and maintaining data pipelines for our Banking, Financial Services, and Insurance (BFSI) business units. You will work within an Azure-first environment, using Azure Data Factory as the core orchestration engine to move, transform, and deliver data that powers regulatory reporting, risk analytics, and customer intelligence.Key ResponsibilitiesPipeline Development & OrchestrationBuild and maintain data pipelines in Azure Data Factory including Linked Services, Datasets, Pipelines, and Mapping Data Flows.Implement incremental/delta load patterns using watermarking, change data capture (CDC), and schedule and event-based triggers.Develop parameterized, reusable pipeline templates to accelerate delivery and reduce duplication. Data Integration & TransformationIntegrate ADF with ADLS Gen2, Azure Synapse Analytics, Azure SQL, and Databricks to support the enterprise data lakehouse architecture.Write transformation logic using SQL, PySpark, and ADF Mapping Data Flows to cleanse, conform, and enrich financial and insurance datasets.Support ingestion from diverse BFSI source systems including core banking platforms, policy administration systems, claims databases, and market data feeds. Data Quality & ComplianceImplement data validation checks, null/duplicate handling, and anomaly alerts within pipeline logic.Ensure pipelines comply with regulatory frameworks relevant to BFSI — including RBI guidelines, IRDAI data standards, GDPR, and SOC 2 controls.Apply PII masking and data classification practices for sensitive financial and customer data, in line with data governance policies. Monitoring, Support & OperationsMonitor pipeline health via Azure Monitor and Log Analytics; set up alerts for failures, latency breaches, and data quality anomalies.Investigate and resolve pipeline failures, data discrepancies, and performance bottlenecks in production environments.Maintain clear documentation of pipeline designs, data flows, transformation logic, and runbooks. Required Qualifications, Experience12+ years of data engineering experience, with at least 3 years of production-grade work in Azure Data Factory.Demonstrated exposure to BFSI data domains — banking transactions, insurance claims, policy data, or regulatory reporting. Azure Data Factory — Core SkillsProficiency with ADF pipeline components: Linked Services, Datasets, Activities (Copy, Data Flow, Execute Pipeline, Web, Lookup, ForEach).Experience configuring Integration Runtimes — Azure IR for cloud-to-cloud and Self-hosted IR for on-premises connectivity.Hands-on with ADF Mapping Data Flows for schema-on-read transformations, joins, aggregations, and conditional splits.Familiarity with ADF CI/CD using Azure DevOps, ARM template exports, and branch-based deployment strategies.