Data Analytics Engineer

• Design and implement sophisticated multivariate regression and nonlinear time-series models, such as ARIMA or Bayesian forecasting, to transform historical retail data into accurate sales forecasts across various regional markets.
• Utilize unsupervised machine learning techniques, including clustering and dimensionality reduction, to analyze transactional datasets, uncover hidden operational inefficiencies, and differentiate regional performance patterns.
• Apply feature engineering and feature selection techniques to improve predictive model accuracy and scalability across enterprise datasets.
• Compare, evaluate, and validate statistical models using quantitative performance metrics such as RMSE, AUC, precision-recall metrics, loss functions, and explained variance to ensure robust, reliable predictions.
• Develop mathematical objective functions and constrained optimization methods to automate dynamic pricing strategies and inventory management, ensuring maximum retail profitability through data-driven decision making.
• Integrate diverse retail technology systems by designing advanced data-transfer and transformation pipelines to create an efficient data-analysis environment. Utilize a combination of ETL (Extract, Transform, Load), ELT (Extract, Load, Transform), and streaming data integration approaches, as appropriate, to support flexible, scalable, and real-time data movement across platforms.
• Develop advanced SQL-based analytical expressions and recursive window functions to seamlessly extract real-time Key Performance Indicators (KPIs) from enterprise repositories.
• Design fast, efficient backend systems and data structures that support up-to-the-moment visual displays, so stakeholders can easily track performance.
• Implement thorough, automated data verification processes, along with checksum-based quality assurance cycles, to ensure the accuracy and integrity of ingested datasets in dynamic management settings.
• Develops detailed technical specifications, including Entity-Relationship Diagrams (ERDs) and data lineage maps, to foster a unified Software Development Life Cycle (SDLC) across the organization's retail operations.

Do you have experience in VBA?, * Proven experience working with cloud platforms such as AWS or Azure for data storage and processing.

• Strong programming skills in Java, Python, Bash (Unix shell), or VBA for automation and custom solutions.
• Hands-on experience with big data frameworks including Hadoop ecosystem components like Spark and Hive.
• Expertise in database design principles for both transactional systems (OLTP) like Oracle or SQL Server and analytical systems (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. Embark on a journey where your technical prowess fuels innovation! We're committed to fostering an environment that values your growth through continuous learning opportunities in cutting-edge technologies like Apache Spark, Hadoop, Azure Data Lake, and more. Join us today to help shape the future of data-driven success!

Pulled from the full job description

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