We’re hiring an experienced Azure Data Engineer to design, build, and scale our next‑generation data platform for private lending. You’ll own robust ETL/ELT pipelines using Azure Data Factory, Databricks (Delta Lake), Synapse Analytics, and ADLS Gen2—integrating structured and semi‑structured data from core lending systems, CRM, payment gateways, credit bureaus, and third‑party REST APIs. You’ll collaborate with data scientists, BI developers, and risk/compliance teams to deliver analytics for risk modeling, portfolio performance, collections, and regulatory reporting.

What You’ll Do (Key Responsibilities)

• Design & Build Pipelines: Develop scalable, secure ADF pipelines and Databricks notebooks for batch and near‑real‑time ingestion and transformations; implement medallion architecture (Bronze/Silver/Gold) on ADLS Gen2/Delta.
  
• REST API Integrations: Implement robust API ingestion with OAuth2, pagination (cursor/offset), retry/backoff, error handling, idempotent upserts, and incremental watermarks.
  
• Data Modeling & ELT: Build curated fact/dimension models (loan, repayment, collateral, delinquency) optimized for Synapse/Power BI; implement SCD Type 2, partitioning, and schema evolution.
  
• SQL Excellence: Author high‑performance T‑SQL (stored procedures, views, indexing strategies, MERGE/upserts) for transformations, reconciliations, and regulatory extracts.
  
• On‑Prem to Cloud: Modernize/replace SSIS packages with ADF/Data Flows or Databricks; orchestrate dependencies and schedules.
  
• CDC & Streaming: Implement CDC from SQL Server or file drops (Auto Loader), handling late‑arriving data and deduplication.
  
• Security & Governance: Apply Managed Identity, Key Vault, RBAC/ACLs, encryption at rest/in transit, and PII controls; integrate with Purview for lineage and catalog.
  
• Observability: Configure Log Analytics, dashboards, and alerting for ADF/Databricks/Synapse; drive reliability and cost optimization.
  
• DevOps: Use Azure DevOps (Git + YAML pipelines) for CI/CD across ADF/Databricks/Synapse; implement environment promotion and configuration as code.
  
• Stakeholder Collaboration: Partner with product, risk, finance, and compliance teams to translate requirements into robust data solutions and SLAs.
  
  

Requirements

• 6–8 years in Data Engineering with at least 3+ years on Azure (ADF, Databricks, Synapse, ADLS Gen2).
  
• Strong SQL/T‑SQL: complex joins, window functions, dynamic SQL, stored procedures, performance tuning, and MERGE/upserts.
  
• Hands‑on with SQL Server and SSIS (migration/modernization to ADF preferred).
  
• Proven REST API integration experience: authentication (OAuth2, client credentials), pagination, throttling/rate limits, retries, and incremental ingestion.
  
• Expertise with Databricks (PySpark) and Delta Lake (ACID, time travel, schema evolution, optimize/vacuum).
  
• Experience building data models and curated layers for BI/analytics; familiarity with Synapse Serverless/Dedicated.
  
• Solid grasp of data quality (validations, reconciliations), error handling, and observability.
  
• Strong understanding of data security (PII, masking, encryption, access controls) and compliance‑oriented design.
  
• CI/CD with Azure DevOps (repos, branching, pull requests, pipelines).
  
• Excellent communication and ownership mindset in cross‑functional environments.
  

• Domain knowledge in lending/fintech, e.g., loan origination/servicing, delinquency, collections, vintage/roll rate analytics, regulatory reporting.
  
• Python for orchestration/helpers, Power BI exposure, or Event Hub/Functions for event ingestion.
  
• Purview (glossary, lineage), Great Expectations/Deequ‑like data quality frameworks.
  
• Cost optimization (cluster sizing, partitioning/file size best practices, serverless vs dedicated trade‑offs).
  
• Experience with infrastructure‑as‑code (Bicep/Terraform) is a plus.