Data Engineer

  Your Role at a Glance

The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and modern data platform components that support enterprise analytics, reporting, and operational data needs. This role plays a key part in evolving the organization’s data architecture from legacy application databases to a modern cloud-based data warehouse built on a medallion architecture. The position requires strong technical expertise in SQL Server, cloud data platforms, and modern ELT practices while working closely with analytics, application development, and business teams to deliver reliable, well-governed data assets. The Data Engineer contributes to the design and implementation of a high-performance data ecosystem that supports advanced analytics, business intelligence, and data-driven decision making. 

  How You’ll Drive Success

Data Pipeline Engineering

• Design, develop, and maintain scalable data pipelines that ingest and transform data from enterprise platforms including NetSuite, Salesforce, HubSpot, and internally developed applications. 
• Develop efficient ELT workflows using modern integration tools such as Fivetran, Integrate.io, Azure Data Factory, or similar technologies to automate data ingestion and transformation. 
• Build and optimize SQL-based transformations and orchestration processes that support reliable and efficient movement of data across the organization’s data platform.

Data Warehouse Architecture and Development 

• Design and implement dimensional data models and curated datasets within a modern medallion architecture data warehouse environment.
• Develop and maintain data layers supporting development, test, and production environments across cloud data platforms including Azure Data Lake, Snowflake, or equivalent platforms.
• Implement scalable data structures and transformation frameworks using SQL, dbt, or similar tools to support high-performance analytics workloads.

Analytics and Business Intelligence Enablement 

• Develop and maintain analytical models including SQL Server Analysis Services (SSAS) cubes and semantic layers supporting enterprise reporting and analytical applications.
• Collaborate with analytics and business intelligence teams to deliver optimized data models and datasets for visualization tools including Power BI and Tableau.
• Ensure the accuracy, integrity, and availability of analytical data assets used across reporting and business intelligence environments.

Data DevOps, Governance, and Platform Operations 

• Implement and support database and data pipeline deployment processes using Visual Studio, Azure DevOps, Azure Git repositories, and Red Gate SQL Change Automation.
• Monitor, troubleshoot, and optimize data platform performance, data pipeline reliability, and data quality across the enterprise data ecosystem.
• Maintain clear documentation of data models, pipelines, architecture, and operational procedures to support maintainability and knowledge sharing.
• Performs other duties as assigned.

  The Talents We’re Seeking

Education

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, Data Science, or a related technical discipline. 

Required Skills

• 4 - 5 years of experience in data engineering, database development, or enterprise data warehousing environments. 
• Demonstrated experience building and maintaining data pipelines and large-scale data integration processes. 
• Experience working with SQL Server, relational database technologies, and modern cloud data platforms. 
• Experience integrating and modeling data from SaaS business applications such as Salesforce, NetSuite, or HubSpot. 
• Experience supporting analytics platforms and business intelligence tools such as SSAS, Power BI, or Tableau. 

Preferred Skills

• Strong SQL development and data modeling skills with the ability to analyze complex data structures and design scalable solutions. 
• Ability to work within a structured development lifecycle utilizing version control, CI/CD pipelines, and DevOps practices. 
• Ability to collaborate effectively with software engineers, analysts, and business stakeholders to deliver reliable and well-governed data solutions. 
• Proficiency with Microsoft Office (Word, Excel and PowerPoint) as well as calculator, telephone systems, company network and familiarity with CRM tools. 
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