Azure Data Engineer

Our client is a SaaS company specializing in developing software to address both core banking and risk management solutions for regional banks in the US., + Design, build, and operationalize Azure-based data platforms supporting company’s suite of products for community banking clients

• Develop and maintain scalable ETL/ELT pipelines to ingest, transform, and curate data from core banking systems, third-party vendors, and internal data sources
• Implement modern data architecture patterns (data lakehouse, medallion architecture, incremental processing, partitioning, and data lifecycle management) using Azure services
• Build and optimize data models and curated datasets to support analytics, reporting, and downstream applications
• Ensure solutions are secure, compliant, and aligned with banking data standards, working closely with client security and IT teams
• Deploy highly available and resilient solutions using Azure-native capabilities, including multi-environment (dev/test/prod) and infrastructure-as-code practices
• Contribute to and evolve reusable data platform patterns, templates, and accelerators to enable rapid deployment across multiple client environments
• Partner with internal and client stakeholders to translate business requirements into scalable data solutions
• Support data quality, observability, and monitoring frameworks to ensure reliability and trust in delivered data products
• Provide documentation, knowledge transfer, and technical guidance to client teams as part of implementation and onboarding

• Strong experience designing and implementing cloud-native data platforms in Azure, including data ingestion, transformation, and storage
• Hands-on experience building ETL/ELT pipelines using tools such as:
• Azure Data Factory pipelines
• Azure Functions or other serverless compute
• SQL-based and/or Spark-based transformations

• Experience working with Azure data services, including: o Azure Data Lake Storage (ADLS Gen2) o Azure SQL Database / Managed Instance o (Nice to have) Azure Databricks or Microsoft Fabric components

• Understanding of data modeling techniques (dimensional modeling, star schemas, curated vs raw layers)
• Experience implementing data governance, lineage, and quality frameworks (e.g., Purview or similar tools)
• Familiarity with secure data architecture patterns, including RBAC, private endpoints, and network isolation in Azure
• Experience with CI/CD and DevOps practices, including automated deployments using Azure DevOps, GitHub Actions, or similar
• Ability to work in client-facing environments, balancing technical execution with communication and collaboration
• Strong problem-solving skills with a focus on performance optimization, scalability, and maintainability Education and Experience
• 4+ years of experience building data platforms in Azure cloud environments
• 6+ years of overall experience in data engineering, data warehousing, or related fields
• Experience working with financial services or regulated data environments is a strong plus (especially banking)
• Azure certifications preferred:
• DP-203: Data Engineering on Microsoft Azure (updated from DP-200/201)

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