Data Engineer - Retail

The Retail Data Engineer plays a critical role in managing the flow, transformation, and integrity of scan-level data within our retail data ecosystem. This role ensures that raw transactional data such as point-of-sale (POS), promotional, loyalty, and product data is clean, consistent, and fit for analysis. This individual will collaborate closely with merchandising, marketing, operations, and analytics teams to deliver trusted data that powers key business decisions in a dynamic retail environment.

What You'll Do:

• Works with business teams (e.g., Category Management, Marketing, Supply Chain) to define and refine data needs.

• Identifies gaps or ambiguities in retail scan data (e.g., barcode inconsistencies, vendor mappings).

• Translates complex retail requirements into technical specifications for data ingestion and transformation.

• Develops, schedules, and optimizes ETL/ELT processes to ingest large volumes of scan data (e.g., from POS, ERP, loyalty programs).

• Applies robust transformation logic to normalize data across vendors, stores, and systems.

• Works with both structured and semi-structured retail datasets (CSV, JSON, EDI, etc.).

• Implements data validation, reconciliation, and anomaly detection for incoming retail data feeds.

• Designs and maintains audit trails and data lineage for scan data.

• Investigates and resolves data discrepancies in collaboration with store systems, IT, and vendors.

• Conducts exploratory data analysis to uncover trends, seasonality, anomalies, and root causes.

• Supports retail performance reporting, promotional effectiveness, and vendor analytics.

• Provides clear documentation and logic traceability for analysts and business users.

• Collaborates with cross-functional teams such as merchandising, inventory, loyalty, and finance to support retail KPIs and data insights.

• Acts as a data subject matter expert for scan and transaction data.

• Provides guidance on best practices for data usage and transformation in retail contexts.

What We're Looking For:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or related field.
• 3–5 years of experience in data engineering, ideally in a retail environment.
• Experience working with scan-level data from large retail chains or CPG vendors.
• Familiarity with retail ERP systems (e.g., SAP, Oracle), merchandising tools, and vendor data feeds.
• Expert-level SQL and experience working with retail schema structures (e.g., SKUs, UPCs, store IDs).
• Proficient in data pipeline and orchestration tools such as dbt, Airflow, Fivetran, or Apache Spark.
• Experience with cloud-based data platforms (Snowflake, Google BigQuery, Azure Synapse, AWS Redshift).
• Familiarity with retail concepts such as POS systems, promotional pricing, markdowns, units vs. dollars sold, sell-through rates, and planogram compliance.
• Understanding of master data management (MDM) for products, stores, and vendors.
• Experience with data profiling and quality frameworks (e.g., Great Expectations, Soda, Monte Carlo).