Data Engineer I - Finance

Total Quality Logistics; Cincinnati (OH); On-site; USD 90,000 - 120,000; Full time

Benefits offered by this job

Health, dental, vision coverage

401(k) with company match

Tuition reimbursement

Employee discounts

Great Place to Work awards

Job summary

Total Quality Logistics is seeking a Data Engineer to support FP&A by building and optimizing SQL views, pipelines, and Power BI reports. You’ll migrate datasets to Microsoft Fabric/Lakehouse and modernize Excel workbooks for scalable, governed financial reporting.

You’ll collaborate across Finance, Data Engineering, BI, and IT, ensuring data accuracy, validation, and timely delivery. This role combines hands-on data work with governance in a growing logistics finance team.

Qualifications

• Bachelor’s degree in computer science, information systems, data engineering, or related field.
• 1+ years of BI, data engineering, or analytics engineering experience with SQL and Power BI.
• Strong SQL skills: joins, aggregations, filtering, transformations, and troubleshooting.
• Working knowledge of Power BI: reports, semantic models, relationships, DAX, Power Query, dashboard troubleshooting.
• Strong Excel skills: formulas, pivots, linked files, structured tables, Power Query, workbook review.

Responsibilities

• Build, maintain, and optimize SQL views, transformations, and pipelines for financial reporting.
• Assist in migrating FP&A datasets from on-premises to Microsoft Fabric/Lakehouse.
• Develop, maintain, and optimize Power BI datasets, semantic models, and reports/dashboards.
• Apply best practices in DAX, modeling, and governance.
• Help modernize complex Excel workbooks using SQL, Power Query, and linked files.
• Perform data quality checks and reconciliation across systems and reports.

Skills

SQL

Power BI

Excel

Data modeling

DAX

Analytics

Communication

Education

Bachelor’s degree in Computer Science or related

Tools

Microsoft Fabric

Lakehouse

Databricks

Azure

Power Query

Tabular Editor

DAX Studio

Git

Power Automate

Job description

About the role:As a Data Engineer you’ll play a critical role within Financial Planning & Analysis (FP&A) responsible for maintaining and improving financial reporting solutions across SQL, Power BI, Microsoft Fabric, Excel, and related data sources. This role helps FP&A produce accurate, reliable, and repeatable reporting by understanding where data originates, how reporting logic is built, and how results should be validated. Working across Finance, Data Engineering, BI, and IT, the role translates defined reporting needs into practical, documented, and maintainable technical solutions. This position contributes directly to an ongoing effort to modernize and centralize financial reporting, reduce reliance on manual processes, and build a scalable, governed data foundation.What’s in it for you:Competitive base salary plus performance-based bonusWork alongside an industry-leading Finance and FP&A teamComprehensive benefits packageHealth, dental, and vision coverage401(k) with company matchTuition reimbursementEmployee discounts and additional perksCertified Great Place to Work with 900+ lifetime workplace awardsStability, growth, and long-term career development at a rapidly growing companyWhat you’ll be doing:SQL & Cloud Data EngineeringBuild, maintain, and optimize SQL views, transformations, and pipelines that support financial reporting.Assist in migrating FP&A datasets from on-premises systems to the Microsoft Fabric/Lakehouse cloud environment.Power BIDevelop, maintain, and optimize Power BI datasets, semantic models, and reports/dashboards.Apply best practices in DAX, modeling, and governance.Excel ModernizationHelp modernize and optimize complex Excel workbooks that rely on SQL, Power Query, and linked files.Support recurring and ad hoc financial reporting for FP&A.Data Quality, QC & ReconciliationPerform quality control (QC) checks with strong attention to detail and accuracy.Perform data validation and reconciliation across systems and reports to ensure consistency.Communicate, troubleshoot, and resolve technical issues impacting reporting accuracy or performance.Support Finance automation and reporting-process improvement initiatives.Assist with dashboard cleanup, report consolidation, and legacy process documentation.Participate in testing and validation of new data sources, semantic models, and enterprise datasets.Provide technical support and guidance to Finance report users.Continue developing skills in SQL, Power BI, and the Microsoft Fabric platform.Perform other duties and responsibilities as assigned.What we’re looking for:Bachelor’s degree in computer science, Information Systems, Data Engineering, or related field.1+ years of experience in BI, data engineering, or analytics engineering, including hands-on work with SQL and Power BI.Proficiency in SQL, including joins, aggregations, filtering logic, data transformations, and query troubleshooting.Working knowledge of Power BI, including reports, semantic models, relationships, DAX, Power Query, and dashboard troubleshooting.Strong Excel skills, including formulas, pivots, linked files, structured tables, Power Query, and workbook review.Ability to investigate reporting discrepancies and trace issues across source data, SQL, Excel, Power BI, and report outputs.Ability to understand and document financial and operational business rules.Strong analytical, reconciliation, and problem-solving skills with attention to accuracy and completeness.Ability to communicate technical findings clearly to both technical and nontechnical audiences.Ability to work in a deadline-driven Finance environment with multiple priorities.Exposure to Microsoft Fabric, Lakehouse, Databricks, Azure, or similar cloud data platforms preferred.Familiarity with Tabular Editor, DAX Studio, Python, Git, or Power Automate is a plus.Where you’ll be: 4289 Ivy Pointe Blvd, Cincinnati, OH 45245Employment visa sponsorship is unavailable for this position. Applicants requiring employment visa sponsorship now or in the future (e.g., F-1 STEM OPT, H-1B, TN, J1 etc.) will not be considered.