Data analytics engineer role at MPR Management LLC focused on applying big data technologies, cloud platforms, and advanced analytics to transform complex data into actionable insights.

Responsibilities

Design and deploy advanced multivariate regression and nonlinear time-series models, including ARIMA or Bayesian forecasting, to convert historical retail data into regional sales forecasts.
Apply unsupervised learning methods such as clustering and dimensionality reduction to transactional data to reveal hidden operational inefficiencies and distinguish regional performance patterns.
Perform feature engineering and feature selection to boost predictive model accuracy and scalability across enterprise datasets.
Benchmark and validate statistical models using metrics like RMSE, AUC, precision-recall, loss functions, and explained variance to ensure robust predictions.
Develop objective functions and constrained optimization approaches to automate dynamic pricing and inventory management, driving profitability through data-informed decisions.
Build data integration pipelines that connect diverse retail systems, employing ETL, ELT, and streaming approaches as appropriate to enable flexible, scalable, real-time data movement.
Create advanced SQL analytical expressions and recursive window functions to extract real-time KPIs from enterprise data stores.
Architect fast, efficient backend data structures to support near real-time visual dashboards for stakeholders.
Implement automated data verification workflows, including checksum-based quality assurance, to maintain accuracy of ingested data in dynamic environments.
Produce detailed technical specifications, including ERDs and data lineage maps, to align SDLC across the organization’s retail operations.

Requirements

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

Technologies

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

Benefits

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

Overview

Join our innovative team as a Data Analytics Engineer and become a key driver of data driven decision making. In this role, you will leverage big data technologies, cloud platforms, and advanced analytics to transform complex data into actionable insights. Your work will support operational optimization, improved customer experiences, and predictive modeling that advances the business in a fast paced environment.

Pay

USD 65,000 - 95,000 per year

Work Location

Hybrid remote in Flint, MI 48507

Data Analytics Engineer

Job Description