Senior Data Engineer – Retail & Omnichannel Analytics

About the role

We are seeking a Senior Data Engineer to design and deliver a next‑generation retail and omnichannel analytics platform. You will lead hands‑on data engineering, enforce platform best practices, and build scalable architectures that enable self‑service analytics and AI‑driven solutions.

Key responsibilities

• Design and implement scalable data ingestion, transformation, and data product frameworks using Databricks and Spark.
• Define Databricks medallion‑layer best practices, governance, and performance standards.
• Build batch and near‑real‑time pipelines, delivering end‑to‑end data products for retail analytics use cases.
• Develop trusted analytical datasets, semantic models, and governed consumption layers.
• Implement data quality, lineage, monitoring, and observability standards.
• Lead proof‑of‑concepts to evaluate and adopt new platform capabilities.
• Define AI SDLC and AI‑assisted development patterns for engineering teams.
• Partner with cross‑functional stakeholders to ensure solution alignment and adoption.
• Mentor engineers on reusable frameworks and operational excellence.

Required profile

• 3+ years of data engineering experience with end‑to‑end analytics lifecycles.
• Strong leadership and mentoring abilities.
• Proven project delivery in enterprise production environments.
• Upper‑intermediate English proficiency (B2).

Required skills

• Advanced Databricks expertise.
• Apache Spark and PySpark for scalable data processing.
• Strong SQL for analytics, modeling, and performance tuning.
• Scala (nice‑to‑have for Spark‑based pipeline development).

What we offer

• International projects with top brands.
• Collaboration with global, diverse teams.
• Healthcare benefits and employee financial programs.
• Paid time off, sick leave, and upskilling opportunities.
• Unlimited access to LinkedIn Learning library (22,000+ courses).
• Global career opportunities and volunteer programs.
• Award‑winning culture recognized by Glassdoor, Newsweek and LinkedIn.