Lead Business Systems Analyst

We are seeking a highly skilled and collaborative Analytics Engineer to join our growing data team. In this role, you will be responsible for designing, building, and maintaining scalable data models and transformation pipelines that power analytics and business intelligence across the organization. You will work closely with data analysts, data engineers, and business stakeholders to ensure data is accurate, accessible, and actionable.

Key Responsibilities

Data Modeling & Transformation

• Develop and maintain modular, well-documented data models using dbt
• Write efficient, maintainable SQL transformations across Snowflake and SQL Server
• Apply best practices in dimensional modeling and ELT architecture

Cloud & Platform Integration

• Build and orchestrate data pipelines using a variety of tools including SSIS, Python, Azure Data Factory or Synapse Pipelines
• Integrate data from various sources including SQL Server, Oracle, Postgres, Snowflake, and Azure Blob Storage

Data Quality & Governance

• Implement data validation tests and monitoring using SSIS, dbt and SQL
• Collaborate with data stewards to ensure data governance, lineage, and compliance
• Maintain clear and up-to-date documentation in Confluence

Testing & Deployment

• Use GitHub for version control and CI/CD pipelines to deploy data pipeline and transformation projects
• Write and maintain unit and integration tests for data transformations
• Participate in code reviews and enforce data engineering standards

Analytics Enablement

• Partner with analysts and business teams to deliver trusted, reusable datasets
• Build and maintain semantic layers and data marts for self-service analytics

Project & Workflow Management

• Track work using Jira and participate in agile ceremonies (sprint planning, retrospectives)
• Document technical decisions, workflows, and architecture in Confluence

Security & Performance

• Monitor and optimize query performance in Snowflake and SQL Server
• Implement role-based access controls and ensure secure data access

Qualifications

• Solid understanding of analytics engineering, data engineering, or BI development
• Strong SQL and SSIS skills, and experience with dbt in a production environment
• Experience with Snowflake, SQL Server, Oracle, and Azure Data Services
• Familiarity with GitHub, CI/CD workflows, and agile project management tools (e.g., Jira)
• Excellent communication and documentation skills

Nice to Have

• Experience with Python or Power BI
• Knowledge of data observability tools (e.g., Monte Carlo, Great Expectations)
• Exposure to data privacy and compliance frameworks (e.g., GDPR, HIPAA)
• Understanding of SDLC and its adaptation to data engineering