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# Senior Data Engineer

- **Company:** Retail Insight
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $125,000.0
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Code Review, Data Architecture, Data Validation, Information Engineering, Extract Transform Load (ETL), Data Transformation, Data Systems, Distributed Computing Environment, Python (Programming Language), Azure Data Lake, SQL Databases, Data Streaming, Azure Service Bus, Azure Data Factory, Apache Spark, Data Lakes, Infrastructure Automation Frameworks, Information Technology, Bicep, Apache Kafka, Terraform, Data Pipelines, Databricks
- **Published:** October 16, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=af18011016b66924

## About the Role

* Solid, demonstrable experience in data engineering, including building and maintaining production-grade Databricks pipelines.
 * Experience with Databricks Unity Catalog and Databricks Asset Bundles.
 * Strong hands-on knowledge of Apache Spark, Delta Lake and Databricks Workflows.
 * Proficiency in Python and SQL, with a good understanding of data modelling, ETL/ELT patterns and distributed data processing.
 * Experience with Azure data platforms, including Azure Data Factory, ADLS Gen2 and Azure DevOps, or equivalent services on AWS or GCP.
 * Experience implementing data quality checks and pipeline monitoring.
 * Strong communication skills and the ability to work effectively with technical and non-technical colleagues.
 * A collaborative approach, ownership of quality outcomes and a drive to learn and improve.
 * A degree in computer science, data engineering or a related field, or equivalent practical experience.
 * Willingness to travel as required.

Bonus points if you also have

 * Familiarity with infrastructure-as-code tools such as Terraform or Bicep.
 * Familiarity with dbt or similar data transformation frameworks.
 * Exposure to real-time streaming technologies such as Kafka or Event Hubs.
 * Exposure to retail or consumer packaged goods (CPG) data, such as point of sale, inventory or supply chain.
 * Experience working directly with clients., This stage explores your experience and the skills most relevant to the role, as well as how you approach your work. Depending on the position, it may include a practical task, presentation or technical assessment. We'll always explain what's involved in advance.

## Description

We're looking for an experienced Senior Data Engineer to build and support the reliable, scalable data systems that power our solutions for US retail clients.

As our US client portfolio grows, you'll work with complex data environments, helping translate business requirements into practical technical solutions. Working closely with our Chicago-based Lead Data Engineer, alongside data scientists, analysts and product teams, you'll build data pipelines and products that help our clients make better decisions.

This is a hands-on role combining strong technical skills with collaboration and clear communication. You'll contribute to the evolution of our data platform, improve reliability and performance, and help maintain high engineering standards.

You'll also work with colleagues and client stakeholders to understand their needs and support successful delivery.

What you'll be doing

 * Building and maintaining scalable data pipelines, developing and optimising batch and streaming workflows for reliability and performance.
 * Contributing to the design and implementation of data architecture.
 * Implementing data quality checks, monitoring and observability across pipelines.
 * Applying security, access control and governance standards established by our platform team.
 * Collaborating with data scientists and analysts to deliver data products that support their work.
 * Working with the Lead Data Engineer to translate business requirements into technical solutions.
 * Participating in code reviews, setting a high bar for engineering quality and contributing to team standards.
 * Helping identify opportunities to optimise cloud costs and platform performance.
 * Contributing to platform documentation, tooling choices and continuous improvement.