Job Title: Azure Data Engineer (Senior 13+ years)
Location : Long Island NY - Must be at client location once in a week
Duration : 12+ Months
Rate: $70/hr. on C2C – Citizen
Client: Domain: Banking - Understanding of banking-specific data models
Technology Stack : Azure Data Factory, ADLS Gen2, Azure Synapse, Azure Databricks, SQL / PySpark, Azure DevOps, Azure Monitor, Azure Key Vault
Domain: Banking - Understanding of banking-specific data models
About the Role
We 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 Responsibilities
- Pipeline Development & Orchestration
- Build 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 & Transformation
- Integrate 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 & Compliance
- Implement 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 & Operations
- Monitor 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, Experience
- 12+ 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 Skills
- Proficiency 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.
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