Retail Insight
Retail Insight
Retail Insight develops AI-driven SaaS for retailers and consumer packaged goods companies. Its platform combines real-time data and machine learning to help teams manage store and omnichannel operations, from product availability and inventory accuracy to waste, markdowns, promotional compliance, and store performance. The tools turn operational data into prioritized actions and automate tasks, supporting quicker decisions across retail operations and revenue growth management. Retail Insight’s work spans retail technology, food and beverage, and logistics.

Senior Data Engineer, Databricks

Build reliable Databricks pipelines and data products for Retail Insight’s US retail clients. Help deliver scalable analytics infrastructure across cloud data platforms.

Сипаттама

  • Build and maintain scalable data pipelines.
  • Improve batch and streaming workflows for reliability and performance.
  • Help design and implement data architecture.
  • Add data quality checks, monitoring, and observability across pipelines.
  • Apply security, access control, and governance standards.
  • Work with data scientists and analysts to deliver data products.
  • Partner with the Lead Data Engineer to turn business needs into technical solutions.
  • Review code and help uphold engineering standards.
  • Find ways to reduce cloud costs and improve platform performance.
  • Improve platform documentation, tooling choices, and engineering practices.
  • Work with colleagues and client stakeholders to understand needs and support delivery.

Талаптар

  • Demonstrated data engineering experience, including building and maintaining production Databricks pipelines.
  • Experience with Databricks Unity Catalog and Databricks Asset Bundles.
  • Hands-on knowledge of Apache Spark, Delta Lake, and Databricks Workflows.
  • Proficiency in Python and SQL.
  • Understanding of data modelling, ETL/ELT patterns, and distributed data processing.
  • Experience with Azure data services such as Azure Data Factory, ADLS Gen2, and Azure DevOps, or equivalent AWS or GCP services.
  • Experience implementing data quality checks and pipeline monitoring.
  • Strong communication skills and the ability to work well with technical and non-technical colleagues.
  • Collaborative working style, ownership of quality outcomes, and motivation to learn and improve.
  • A degree in computer science, data engineering, or a related field, or equivalent practical experience.
  • Willingness to travel as required.
  • Terraform or Bicep familiarity is a bonus.
  • Familiarity with dbt or a similar data transformation framework is a bonus.
  • Exposure to Kafka or Event Hubs is a bonus.
  • Exposure to retail or CPG data is a bonus.
  • Direct client experience is a bonus.

Артықшылықтар

  • Work-from-anywhere benefits.
  • Summer working hours.
  • Extra time off for major life events, including birthdays and weddings.
  • 26 days of paid time off, accrued with service.
  • Paid volunteer days.
  • Mental health resources.
  • Access to a leading learning platform.
  • Career progression plans.
  • Support for creating a home workspace suited to you.
  • Medical, dental, and vision coverage.
  • Retirement plan with a 6% employer match.
  • Annual phone reimbursement.
  • Access to an onsite gym.
  • Customisable benefits through an online platform.

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