Senior Pricing & Data Expert Retail

Project overview

For a large retail company (omnichannel, data-driven price and assortment management), we are looking for a Senior Data Engineer / Analytics Engineer with a strong business focus to support the Pricing and Category Management departments.

YOUR CHALLENGE

YOUR TALENTS

• Start: ASAP
• Duration: 6 months (option to extend)
• Remote/On-Site: Hybrid (approx. 60-80% remote)
• Utilization: 4-5 days/week (80-100%)
• End-to-end implementation of pricing and category management use cases: from requirements gathering to productive dashboards
• Development, optimization, and operation of high-performance SQL/Python-based ETL processes for preparing large amounts of data (including competitor data)
• Analysis of existing KNIME workflows and gradual migration to Databricks, including stabilization and documentation
• Maintenance and further development of a Bronze/Silver/Gold data model (building new Gold tables, replacing/archiving legacy tables)
• Establishment of automated data quality checks (plausibility, outlier detection, rule sets) and definition of error handling measures
• Development and optimization of Power BI dashboards (new & existing), including KPI definition, data model design, and performance tuning
• Improvement of DAX performance and reduction of loading times through pre-aggregation and sensible data provisioning
• Provision of reliable analyses on price/margin/competitor development, category performance, inventory, and product performance
• Close collaboration with business departments: challenging requirements, evaluating technical feasibility, and establishing pragmatic compromises between wishes and performance
• Must-have: 5+ years of experience in Data Engineering / Analytics Engineering with demonstrable end-to-end responsibility
• Must-have: very strong SQL skills (modeling, performance optimization, complex transformations)
• Must-have: very good Power BI skills (data modeling, KPI logic, DAX, performance optimization)
• Must-have: Python for data wrangling, statistical analysis, clustering/similarity approaches, and outlier detection (without research focus)
• Must-have: experience with data quality management (automated checks, monitoring, handling of erroneous outliers in source systems)
• Must-have: strong stakeholder and requirements management (e.g., Jira), consulting and communication skills
• Desirable: experience with Databricks and/or Cloud Data Platforms as well as Lakehouse/Medallion approaches
• Desirable: migration projects from low-/no-code tools (e.g., KNIME) to scalable platforms
• Desirable: domain knowledge in retail, especially pricing, competitor data, and product/category data models
• No focus: Deep Learning, Data Science Research, AI model development, or forecasting (covered by existing systems)

Project details

• Start: flexible
• Location: DE
• Languages: German