Data Analytics Engineer

Job DescriptionJob DescriptionMidwest Railcar - Data Analytics Engineer About Midwest Railcar LLC - Midwest Railcar, LLC, a company related to Imperial PFS (IPFS), is a premier railcar leasing and rail fleet management company serving a diverse range of industries, including agriculture, energy, construction materials, iron & steel, chemicals, plastics, food products, and many others. The company owns, leases, and manages a fleet of more than 31,000 railcars, offering a broad range of equipment including covered hoppers, gondolas, tank cars, boxcars, open top hoppers, and flatcars through flexible leasing solutions tailored to meet customer needs. Backed by strong capital partners and deep industry expertise, Midwest Railcar combines high-quality equipment, disciplined asset management, and a customer-focused approach to ensure long-term value, performance, and sustainable growth.Compensation and BenefitsCompensation annual salary range of $88,000 to $117,000Medical, dental, vision and life insurance plans401(k) planGenerous paid time off (PTO) planCompany-paid holidays About the RoleThe Data Analytics Engineer builds and maintains the foundational data infrastructure that transforms raw business data into reliable, analysis-ready insights for decision-making. This position is critical to establishing scalable data models, pipelines, and governance practices that will support our growing analytical needs.The prime reason for this role's existence is to bridge the gap between raw data ingestion and analytics needs, ensuring that our analysts and stakeholders have access to high-quality, well-documented, and performant data models. This position directly contributes to the company's overall mission by enabling data-driven decision making across all departments, improving operational efficiency, and supporting strategic initiatives through reliable analytics infrastructure.Key contributions to the company include:Building standardized data models that reduce time-to-insight for business usersImplementing data quality and governance frameworks that ensure information is accurate and compliant.Creating reliable, well-documented data pipelines that enable consistent reporting and analytics across all business functions What You'll DoData Modeling and Pipeline DevelopmentDesign, build, and manage data models and ELT/ETL pipelines to transform raw data into structured formats within Snowflake using dbtCreate conform and analytics layers that standardize data for business consumptionDevelop dimensional models and data marts tailored to business requirementsData Quality and GovernanceImplement best practices for data quality, integrity, and performance monitoringContribute to data governance frameworks, including maintaining data lineage and definitionsEstablish data quality checks and validation processes within dbt workflowsPerformance OptimizationOptimize data storage and retrieval processes within Snowflake to ensure scalable, reliable, and cost-effective data solutionsFine-tune SQL queries and data transformations for optimal performanceMonitor and improve pipeline efficiency and resource utilizationTechnical DocumentationCreate and maintain clear, comprehensive documentation for data models, processes, and key metricsDocument data lineage and maintain metadata for analytical datasetsEstablish documentation standards and best practices for the teamSoftware Engineering PracticesLeverage version control and CI/CD pipelines for streamlined, reliable development processesEnsure code quality through testing, peer reviews, and automated deploymentCollaboration and Stakeholder ManagementWork closely with analysts and business subject matter experts to understand requirementsTranslate business needs into effective technical data solutionsParticipate in regular stakeholder meetings to refine and expand data capabilities Other Tasks and Responsibilities as RequiredRequired QualificationsBachelor’s degree in Information Systems or a related field2-4 years of experience in analytics engineering, data engineering, or similar roleAdvanced SQL proficiency in ANSI-SQL for querying, data transformation, and building data infrastructureSnowflake expertise with hands-on experience in its architecture and best practices for data management and processingStrong data modeling skills with deep understanding of data modeling principles and experience designing efficient structures for analyticsdbt proficiency for managing data transformations and building data models within SnowflakePassion for detail and quality - skilled at spotting data and process gaps and committed to driving continuous improvementStrong communication skills and comfort collaborating with non-technical stakeholdersIntellectual curiosity and drive to understand business problems through dataCommunication skills – specifically 1 on 1 communication skills with staff regarding changes or fixes that could affect them.Listening skills – being able to interpret the issues that the user is facing is key when providing them with a solution.Understand and prioritize corporate goalsPreferred QualificationsSnowPro certification or equivalent advanced Snowflake expertiseExperience with modern cloud data architecture (data lakes, data lakehouses, cloud data platforms)Experience with ELT/ETL tools (Fivetran experience a plus)Knowledge of data visualization tools (Tableau, Looker, Power BI)Previous experience in insurance, finance, or regulated industriesPython programming experience for data parsing, transformation, and scripting within data pipelines The salary range for this position is $88,000 to $117,000. If an offer is made, the pay rate determinations will take into account relevant market data and the applicant’s prior experience, education and other qualifications directly related to the position to ensure internal equity.