Data Warehouse Engineer

Veriipro; United States; On-site; USD 120,000 - 190,000; Full time

Job summary

Veriipro is seeking a data warehouse architect/engineer to design and implement scalable cloud data warehouse solutions on Azure Synapse, establishing a single source of truth across the enterprise.

You will optimize ETL/ELT pipelines with ADF and Databricks, integrate structured and unstructured data, modernize legacy systems, and drive CI/CD, collaboration with stakeholders, and technical leadership.

Qualifications

• Strong experience designing scalable cloud data warehouse solutions on Azure.
• Establish enterprise data warehouse architecture as a single source of truth.
• Develop dimensional models for BI reporting and analytics.
• Build ETL/ELT pipelines with Azure Data Factory and Azure Databricks.
• Ingest and transform data into Azure Data Lake and Synapse.
• Optimize SQL queries and performance with indexing and partitioning.
• Ensure high availability and scalability of data warehouses.
• Integrate structured and unstructured data within Azure.
• Modernize legacy mainframe systems (COBOL, JCL, CICS/IMS, DB2, VSAM).
• Implement CI/CD pipelines using Git, Jenkins, GitHub, or Azure DevOps.
• Provide release management and version control across data initiatives.
• Collaborate with stakeholders to translate requirements into scalable data solutions.

Responsibilities

• Design scalable cloud data warehouse solutions on Azure Synapse.
• Define enterprise DW architecture as a single source of truth.
• Develop dimensional models for BI reporting.
• Build ETL/ELT pipelines with ADF and Databricks.
• Ingest and transform data into Azure Data Lake and Synapse.
• Optimize SQL queries and performance via indexing and partitioning.
• Ensure high availability and scalability of DW solutions.
• Integrate structured and unstructured data in Azure.
• Modernize legacy mainframe systems (COBOL, JCL, CICS/IMS, DB2, VSAM).
• Implement CI/CD pipelines using Git/Jenkins/GitHub/Azure DevOps.
• Ensure automated deployments and release management.
• Collaborate with stakeholders to translate requirements into scalable data solutions.
• Provide technical leadership across data initiatives.

Skills

SQL performance tuning

Dimensional data modeling

Medallion architecture

Stakeholder management

Data integration

Analytical thinking

Mainframe modernization

Tools

Azure Synapse Analytics

Azure Data Factory

Azure Databricks

Azure Data Lake Storage Gen2

SSRS

Azure Analysis Services

Git

Jenkins

GitHub

Azure DevOps

Job description

Roles & Responsibilities

• Design and implement scalable cloud-based data warehouse solutions using Azure Synapse Analytics
• Define and maintain enterprise data warehouse architecture as a single source of truth
• Develop and optimize dimensional data models (fact/dimension tables) for BI reporting
• Build and maintain ETL/ELT pipelines using Azure Data Factory and Azure Databricks
• Ingest, transform, and load data from multiple structured and unstructured sources into Azure Data Lake and Synapse
• Optimize SQL queries and manage database performance through indexing, partitioning, and compute tuning
• Ensure high availability and scalability of data warehouse solutions
• Integrate relational and non-relational data within Azure ecosystem
• Analyze and modernize legacy mainframe systems including COBOL, JCL, CICS/IMS, DB2, and VSAM
• Implement CI/CD pipelines using Git, Jenkins, GitHub, or Azure DevOps
• Ensure version control, automated deployments, and release management
• Collaborate with business and technical stakeholders to translate requirements into scalable data solutions
• Provide technical leadership and problem-solving support across data initiatives

Required Skills

• Strong experience with SSRS, Databricks, Azure Data Lake Storage Gen2, Azure Analysis Services
• Hands-on experience with Azure Synapse Analytics (SQL Data Warehouse)
• Expertise in Azure Data Factory (ADF) and/or Azure Databricks for ETL/ELT pipelines
• Strong knowledge of SQL performance tuning, indexing, partitioning, and query optimization
• Experience implementing CI/CD pipelines using Git, Jenkins, GitHub, or Azure DevOps
• Strong understanding of dimensional data modeling (fact & dimension tables) and Medallion architecture (Gold layer)
• Experience integrating structured and unstructured data using Azure Data Lake
• Strong analytical, communication, and stakeholder management skills
• Experience analyzing mainframe legacy systems (COBOL, JCL, CICS/IMS, DB2, VSAM)