Data Engineer (Data Lake)

Senior Data Engineer / Data Architect

We are seeking an experienced Senior Data Engineer / Data Architect to evaluate and enhance an enterprise-scale data platform while driving modernization, governance, and long-term architecture strategy. This role will be responsible for assessing current data lake environments, designing scalable data solutions, improving data quality and security controls, and supporting modern analytics platforms within the Microsoft data ecosystem.

The ideal candidate combines deep hands-on engineering expertise with architectural leadership, strong governance practices, and the ability to collaborate across technical and business teams. Experience with Snowflake is considered a plus for organizations evaluating hybrid or multi-platform data strategies.

Key Responsibilities

• 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 that support scalability, performance, governance, and long-term platform modernization.


• Design, develop, and maintain robust data pipelines and integration solutions that deliver trusted, high-quality data for reporting, analytics, and business operations.


• 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 that support 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.

Required Qualifications

• 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
  
  
  • Azure Synapse Analytics
  
  
  • Azure Data Lake Storage (ADLS Gen2)
  
  
  • OneLake
  
  
  • Power BI
  
  
  • Power Automate
  
  
  • Microsoft Purview
  
  
  • 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 with the ability to explain complex technical concepts, architecture decisions, risks, and implementation strategies to diverse stakeholders.

Preferred Qualifications

• Experience with DevOps practices for enterprise data platforms, including:
  
  
  
  • Git-based source control
  
  
  • CI/CD pipelines
  
  
  • Automated deployments
  
  
  • Environment promotion strategies
  
  
  • Rollback planning
  
  
  • Separation-of-duties controls
  
  
  
  


• Familiarity with Snowflake architecture and administration, including performance optimization, workload management, governance, security, and cost management.


• Experience evaluating and comparing cloud data platforms for scalability, governance, interoperability, performance, and long-term architecture strategy.


• Knowledge of data privacy regulations, security frameworks, compliance requirements, and audit-ready controls for sensitive enterprise data.

Preferred Certifications

• Microsoft Certified: Fabric Data Engineer Associate


• Microsoft Certified: Fabric Analytics Engineer Associate


• Microsoft Certified: Azure Solutions Architect Expert


• Microsoft Certified: Power BI Data Analyst Associate


• Microsoft certifications related to Microsoft Purview, Information Protection, Data Governance, Security, Privacy, or Compliance


• Microsoft Azure Fundamentals, Data Fundamentals, or Security Fundamentals


• Snowflake SnowPro Core, SnowPro Advanced Data Engineer, SnowPro Advanced Architect, or similar cloud data platform certifications