The posting
As the Associate Analytics Engineer at Integrity, you are responsible for supporting the development, maintenance, testing, and improvement of data models and analytics solutions that drive business intelligence and operational decision-making. Working with data architects, engineers, analysts, and business partners, this role transforms complex data into reliable, actionable insights.
The position supports data integration, transformation, modeling, validation, and reporting using tools such as Fivetran, Snowflake, dbt Cloud, Power BI, and Microsoft Fabric. It partners with Finance, Accounting, Sales, Operations, and Technology to develop scalable analytics solutions, resolve data issues, and improve processes.
This position reports to the Data Analytics Manager.
Core Responsibilities
Data Modeling & Transformation
- Develop, maintain, test, and enhance data models and transformation processes to support business intelligence, analytics, and reporting needs.
- Build and maintain dbt models across staging, intermediate, and mart layers, incorporating appropriate testing, documentation, and data quality standards.
- Write, optimize, and maintain SQL queries and data transformations within Snowflake to support accurate, reliable, and efficient data processing.
- Assist in optimizing Snowflake queries, incremental models, and warehouse utilization to improve performance and manage costs.
Data Integration & Pipeline Support
- Support data integration processes using Fivetran, including monitoring synchronization, configuring tables and columns, troubleshooting missing data, and assisting with historical re-synchronization.
- Monitor data transformation processes and pipeline performance, troubleshoot failures, and assist in resolving synchronization, performance, and data quality issues.
- Support data refresh processes and orchestration using Power BI, Microsoft Fabric, and other applicable technologies.
Business Intelligence & Analytics
- Assist in developing and maintaining Power BI semantic models, dashboards, and reports using dimensional modeling, DAX measures, and appropriate data security practices.
- Support the development and maintenance of trusted business metrics related to load profitability, accounts receivable, accounts payable, commissions, carrier payments, and other operational and financial activities.
- Collaborate with business stakeholders to understand reporting and analytics requirements and translate those needs into reliable data models, standardized metrics, and analytics solutions.
Data Quality & Validation
- Validate transformed data against source systems and accounting records to identify discrepancies, investigate root causes, and assist with implementing appropriate corrections.
- Perform data quality testing and reconciliation to support the accuracy, completeness, and consistency of business information.
- Create and maintain technical documentation for data models, transformation logic, metric definitions, data lineage, and troubleshooting procedures.
Collaboration & Development Practices
- Collaborate with data architects, engineers, analysts, and cross-functional business partners to support consistent, scalable, and maintainable analytics solutions.
- Participate in code reviews, version control, and collaborative development processes using GitHub and established development standards.
- Participate in Agile development activities, project planning, testing, and implementation of new analytics solutions.
Process Improvement & Professional Development
- Identify opportunities to automate manual processes, improve data reliability, enhance reporting consistency, and increase overall data accessibility.
- Recommend improvements to existing data models, transformation processes, and analytics workflows to support operational efficiency.
- Develop technical expertise across IEL's analytics engineering platforms and progressively assume responsibility for more complex assignments.
- Perform other duties as assigned.
Knowledge, Skills, & Experience
Required Qualifications
- Bachelor's degree in Computer Science, Information Systems, Data Analytics, Statistics, Informatics, or a related quantitative field, or an equivalent combination of education and relevant experience.
- 1-3 years of relevant experience in analytics engineering, data engineering, data analytics, business intelligence, or a related technical discipline. Relevant internships, academic projects, or equivalent practical experience will be considered.
- Strong foundational SQL knowledge, including experience querying relational databases, developing queries, and working with complex datasets.
- Understanding of data transformation, data modeling, and data warehousing concepts, including ETL/ELT processes.
- Familiarity with cloud-based data platforms and business intelligence tools.
- Basic understanding of relational database structures, dimensional modeling, and data validation principles.
- Understanding of data quality practices, including testing, reconciliation, and documentation.
- Strong analytical and problem-solving skills, including the ability to investigate data discrepancies and identify potential solutions.
- Strong organizational skills with the ability to manage multiple priorities, meet deadlines, and maintain attention to detail.
- Ability to interpret business requirements and assist in translating them into technical data and analytics solutions.
- Effective written and verbal communication skills, including the ability to explain technical information to non-technical stakeholders.
- Ability to collaborate effectively with cross-functional teams in a dynamic environment.
- Ability to complete assigned tasks independently while recognizing when guidance or additional support is needed.
- Willingness and ability to learn new technologies, development practices, and analytics engineering methodologies.
Preferred Qualifications
- Experience with dbt or dbt Cloud, including layered data modeling, incremental models, Jinja, macros, automated testing, documentation, or scheduled jobs.
- Experience with Snowflake, including advanced SQL, window functions, QUALIFY, JSON or semi-structured data, query optimization, and warehouse management.
- Experience with Fivetran, including connector configuration, synchronization monitoring, troubleshooting, or historical re-synchronization.
- Experience with Power BI, including DAX, Power Query (M), star schemas, row-level security, incremental refresh, or troubleshooting refresh failures.
- Familiarity with Microsoft Fabric, including Data Factory pipelines, data orchestration, and capacity management.
- Experience with PostgreSQL, NoSQL, or other relational or application databases.
- Experience using GitHub or similar version control tools, including pull requests and code reviews.
- Experience with Python for data analysis, automation, or development of supporting tools.
- Familiarity with data structures, metadata management, data lineage, dependency management, and workload optimization.
- Exposure to machine learning concepts or applications.
- Familiarity with accounting or ERP data, including accounts payable, accounts receivable, general ledger, or Sage Intacct.
- Experience working in an Agile development environment.
- Experience in the third-party logistics (3PL), freight brokerage, transportation, or supply chain industry.
- Familiarity with transportation management systems (TMS) and logistics-related data.
Physical Requirements
- Ability to sit or stand at a desk for prolonged periods of time.
- Ability to lift up to 15 lbs.
We are committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at [email protected] or call 1-888-374-5138 ext. 4.
