Data Engineer; Data Lake

This contract Senior Data Engineer / Data Architect position focuses on evaluating and improving an enterprise-scale data platform, with an emphasis on modernizing data lake environments. The role will help establish governance, security, data quality, and scalable data pipelines across a Microsoft-centric data ecosystem.

Assess current enterprise data environments and lead architecture improvements that strengthen scalability, performance, governance, and long-term platform modernization. The position also supports secure integration and pipeline delivery for reporting, analytics, and business operations, while contributing to technology evaluation across cloud data warehousing and lakehouse options.

• Assess existing enterprise data environments, including data lake architecture, ingestion frameworks, transformation processes, security models, lineage, and operational support practices.
• Lead architecture reviews and recommend improvements to support scalability, performance, governance, and long-term platform modernization.
• Design, develop, and maintain robust data pipelines and integration solutions delivering trusted, high-quality data.
• Establish and enhance data governance processes, including metadata management, cataloging, data lineage, data quality monitoring, sensitivity classification, and access controls.
• Collaborate with business stakeholders, data stewards, infrastructure teams, security teams, and application owners to deliver secure and scalable data solutions.
• Implement and maintain controls for data privacy, regulatory compliance, audit readiness, and enterprise security requirements.
• Define operational standards for monitoring, alerting, troubleshooting, performance optimization, deployment validation, and production support.
• Provide technical leadership through architecture guidance, code reviews, mentoring, and knowledge transfer across data engineering and analytics teams.
• Create and maintain architecture documentation, technical standards, governance procedures, implementation roadmaps, and executive-level recommendations.
• Support evaluation of cloud data warehousing and lakehouse technologies, including interoperability, scalability, governance, and cost optimization considerations.

• Bachelor's degree in Computer Science, Information Technology, or a related field.
• 7+ years of experience in data engineering, data architecture, business intelligence engineering, or enterprise data platform development.
• Strong experience with Microsoft Fabric
  .
• Strong experience with Azure Synapse Analytics
  .
• Strong experience with Azure Data Lake Storage (ADLS Gen2).
• Strong experience with One Lake
  .
• Strong experience with Power BI
  .
• Strong experience with Power Automate
  .
• Strong experience with Microsoft Purview
  .
• Strong experience with Azure-based data integration and analytics services
  .
• Deep understanding of data lake architecture, lakehouse methodologies, data warehousing, dimensional modeling, semantic modeling, metadata management, and enterprise governance frameworks.
• Experience leading architecture assessments, defining future-state solutions, creating technology roadmaps, and presenting recommendations to technical and executive audiences.
• Advanced SQL expertise and hands-on experience with ETL/ELT development, orchestration, data modeling, performance tuning, data validation, and issue resolution.
• Strong understanding of governance and security controls, including role-based access, data classification, lineage, cataloging, audit logging, and change management.
• Proven ability to mentor engineers, lead design reviews, establish engineering standards, and promote best practices across teams.
• Excellent communication skills, including the ability to explain complex technical concepts, architecture decisions, risks, and implementation strategies to diverse stakeholders.

• Experience with Dev Ops practices for enterprise data platforms, including Git-based source control.
• Experience with Dev Ops practices for enterprise data platforms, including CI/CD pipelines.
• Experience with Dev Ops practices for enterprise data platforms, including automated deployments.
• Experience with Dev Ops practices for enterprise data platforms, including environment promotion strategies.
• Experience with Dev Ops practices for enterprise data platforms, including rollback planning.
• Experience with Dev Ops practices for enterprise data platforms, including separation-of-duties controls.
• Familiarity…