Data Analytics Engineer

Benefits and culture

Join a data-driven team that values practical analytics and collaboration. This hybrid role in Flint, Michigan offers a comprehensive benefits package and a work environment that supports growth and flexible scheduling.

• Dental insurance
• Health insurance
• Flexible schedule
• Paid time off
• Parental leave
• Retirement plan
• Tuition reimbursement

Overview

In this Data Analytics Engineer position, you will apply big data technologies, cloud platforms, and advanced analytics to convert complex data into actionable insights. The role emphasizes forecasting, optimization, and data driven decision making to improve operations and customer experiences.

Responsibilities

• Design and implement multivariate regression and nonlinear time-series models, such as ARIMA or Bayesian forecasting, to generate sales forecasts across regional markets from historical retail data.
• Apply unsupervised machine learning techniques, including clustering and dimensionality reduction, to analyze transactional datasets, uncover operational inefficiencies, and differentiate regional performance patterns.
• Use feature engineering and feature selection techniques to improve predictive model accuracy and scalability across enterprise datasets.
• Compare, evaluate, and validate statistical models using metrics such as RMSE, AUC, precision-recall, loss functions, and explained variance to ensure robust predictions.
• Develop mathematical objective functions and constrained optimization methods to automate dynamic pricing strategies and inventory management, maximizing retail profitability through data-driven decisions.
• Integrate diverse retail technology systems by designing data-transfer and transformation pipelines to create an efficient data-analysis environment. Utilize ETL, ELT, and streaming data integration approaches as appropriate for flexible, scalable, and real-time data movement across platforms.
• Develop advanced SQL-based analytical expressions and recursive window functions to extract real-time KPIs from enterprise repositories.
• Design fast, efficient backend systems and data structures that support up-to-the-moment visual displays for stakeholder visibility.
• Implement automated data verification processes, along with checksum-based quality assurance cycles, to ensure accuracy and integrity of ingested datasets in dynamic management settings.
• Develop detailed technical specifications, including ERDs and data lineage maps, to foster unified SDLC practices across the organization’s retail operations.

Requirements

• Proven experience with cloud platforms such as AWS or Azure for data storage and processing.
• Strong programming skills in Java for automation and custom solutions.
• Strong programming skills in Python for automation and custom solutions.
• Strong programming skills in Bash (Unix shell) for automation and custom solutions.
• Strong programming skills in VBA for automation and custom solutions.
• Hands-on experience with big data frameworks including Hadoop, Spark, and Hive.
• Expertise in database design principles for OLTP such as Oracle or SQL Server and OLAP such as data warehouses.
• Familiarity with ETL tools like Talend or Informatica for efficient data integration workflows.
• Knowledge of Linked Data principles for connecting disparate datasets across platforms.
• Demonstrated ability to analyze complex datasets with excellent analysis skills to identify trends and insights.
• Experience working within Agile teams to deliver iterative solutions rapidly while maintaining high quality standards.

Technologies

• AWS
• Azure
• Java
• Python
• Bash (Unix shell)
• VBA
• Hadoop
• Spark
• Hive
• Oracle
• SQL Server
• Talend
• Informatica
• Azure Data Lake
• SQL

Compensation

Salary: USD 65,000 - 95,000 per year

Location

Location: Flint, MI (hybrid)