Analytics Engineer, Associate

Integrity Express Logistics•Cincinnati, OH

16d

About The Position

The Associate Analytics Engineer supports the development, maintenance, testing, and improvement of data models and analytics solutions that inform 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. The role develops and maintains dbt models, SQL transformations, and Snowflake workflows; supports Fivetran integrations and data pipelines; and assists with Power BI semantic models, dashboards, reports, and trusted business metrics. It validates data against source systems and accounting records, performs quality testing and reconciliation, and documents models, logic, metric definitions, lineage, and troubleshooting procedures. The Associate Analytics Engineer also participates in code reviews, version control, Agile development, and process improvement, while developing technical expertise and taking on progressively more complex assignments. The position requires a bachelor's degree in a related quantitative or technical field, or equivalent education and relevant experience, and 1–3 years of relevant experience. Relevant internships, academic projects, or equivalent practical experience may be considered. Preferred qualifications include experience with dbt, Snowflake, Fivetran, Power BI, Microsoft Fabric, databases, GitHub, Python, accounting or ERP data, Agile practices, and logistics or transportation systems and data. Physical requirements include the ability to sit or stand at a desk for prolonged periods and lift up to 15 pounds. The employer states it will provide reasonable accommodations for qualified individuals with disabilities in its application procedures and describes its equal employment opportunity commitment for U.S.-based employees.

Requirements

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 querying relational databases, developing queries, and working with complex datasets.
Understanding of data transformation, data modeling, data warehousing, and 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 investigating data discrepancies and identifying potential solutions.
Strong organizational skills, ability to manage multiple priorities and meet deadlines, and 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 explaining 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.

Nice To Haves

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.

Responsibilities

Develop, maintain, test, and enhance data models and transformation processes for business intelligence, analytics, and reporting.
Build and maintain dbt models across staging, intermediate, and mart layers, with appropriate testing, documentation, and data quality standards.
Write, optimize, and maintain SQL queries and data transformations in Snowflake.
Assist with optimizing Snowflake queries, incremental models, and warehouse utilization to improve performance and manage costs.
Support Fivetran data integrations by 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 help resolve synchronization, performance, and data quality issues.
Support data refresh processes and orchestration using Power BI, Microsoft Fabric, and other applicable technologies.
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 for 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 them into reliable data models, standardized metrics, and analytics solutions.
Validate transformed data against source systems and accounting records, investigate discrepancies and root causes, and assist with 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.
Collaborate with data architects, engineers, analysts, and cross-functional business partners on consistent, scalable, and maintainable analytics solutions.
Participate in code reviews, version control, and collaborative development using GitHub and established development standards.
Participate in Agile development activities, project planning, testing, and implementation of analytics solutions.
Identify opportunities to automate manual processes, improve data reliability and reporting consistency, and increase data accessibility.
Recommend improvements to data models, transformation processes, and analytics workflows to support operational efficiency.
Develop expertise across IEL's analytics engineering platforms and progressively take responsibility for more complex assignments.
Perform other duties as assigned.