Sr. Data Engineer

Carhartt is seeking a Senior Data Engineer to design, build, optimize, and support secure, reliable, and scalable enterprise data solutions. This role provides technical leadership across Azure Databricks and Lakehouse architecture, with a focus on production-ready data pipelines, governed data products, and AI/ML-ready datasets. The position is based in Dearborn, MI with a remote work classification.

What you will do

• Design, develop, test, deploy, and support scalable batch and streaming data pipelines using Azure Databricks, Azure Data Factory, Python, PySpark, SQL, and related cloud-native services.
• Design and evolve Lakehouse architecture using Delta Lake and Azure Data Lake Storage, including reusable data products and medallion-oriented layers where appropriate.
• Create and optimize data models spanning conceptual, logical, dimensional, relational, and physical levels aligned to business meaning and analytics needs.
• Optimize pipelines, SQL queries, clusters, storage layouts, and processing patterns for performance, reliability, scalability, and cost effectiveness.
• Implement orchestration and production controls including dependency management, scheduling, monitoring, logging, alerting, error handling, recovery, lineage, and observability.
• Apply data governance and quality practices such as metadata and cataloging, validation and reconciliation, security and privacy, retention, and access controls.
• Engineer trusted, well-documented, reusable datasets and features to support reporting, advanced analytics, data science, and AI/ML use cases.
• Lead technical design discussions, establish engineering standards and reusable patterns, conduct code and design reviews, and document architectural decisions and tradeoffs.
• Mentor data engineers through pairing, technical guidance, code reviews, troubleshooting, coaching, and clear documentation.
• Partner with business stakeholders, analysts, data scientists, product owners, architects, security teams, application teams, and vendors throughout the solution life cycle.
• Apply software engineering practices including Git-based source control, automated testing, CI/CD, deployment automation, and infrastructure configuration.
• Provide advanced production support including root-cause analysis, corrective actions, and continuous improvement for complex data platform and pipeline incidents.

What you bring

• Bachelor’s Degree in Computer Science, Information Systems, Engineering, Data Science, or a related technical field (or equivalent related experience).
• Graduate degree preferred.
• Minimum of 8 years of professional experience in data engineering, data warehousing, business intelligence, cloud data platforms, or a related field.
• Demonstrated experience designing, implementing, and supporting enterprise data solutions using Azure Databricks and Lakehouse architecture.
• Advanced experience with data pipeline design and orchestration across batch and streaming patterns, including dependencies, scheduling, monitoring, and recovery.
• Advanced SQL skills, including data modeling, query optimization, performance troubleshooting, and complex analytical transformations.
• Professional experience with Python and distributed data processing frameworks such as PySpark.
• Experience with Azure Databricks, Delta Lake, Azure Data Lake Storage (ADLS), Azure Data Factory (ADF), Unity Catalog, Azure DevOps, and related Microsoft Azure data platform services.
• Experience designing conceptual, logical, dimensional, relational, and physical data models for analytical and operational use.
• Experience optimizing cloud workloads for performance, scalability, reliability, and cost effectiveness.
• Working knowledge of data governance concepts including metadata, cataloging, lineage, data quality, security, privacy, retention, and access control.
• Experience preparing trusted, governed, reusable, and well-documented data products enabling reporting, advanced analytics, data science, machine learning, generative AI, and future AI-driven business capabilities.
• Experience with Git-based development, code reviews, automated testing, CI/CD, and deployment automation.
• Experience integrating data from SAP, SAP Datasphere, APIs, files, events, product and master data platforms, and third-party enterprise systems.
• Demonstrated technical leadership through architecture and solution design, engineering standards and best practices, design reviews, mentoring, code reviews, reusable patterns, and technical guidance.
• Excellent verbal and written communication skills, including explaining technical designs, risks, decisions, and tradeoffs to technical and business audiences.
• Strong cross-functional collaboration with business partners, analysts, data scientists, product owners, architects, security teams, and application teams.
• Ability to isolate complex problems, evaluate options, make practical decisions, and provide advanced production support during critical incidents.
• Professional cloud or data engineering certification considered a plus.

Technologies

• Azure Databricks, Azure Data Factory, Python, PySpark, SQL
• Delta Lake, Azure Data Lake Storage (ADLS), Unity Catalog
• Azure DevOps, Git-based source control, CI/CD
• SAP, SAP Datasphere, APIs

Benefits

• Comprehensive suite of medical, dental, and vision insurance
• Short-term and long-term disability insurance
• Life insurance
• Employee assistance program
• 401(k) plan with employer matching contributions
• Paid time off and designated paid holidays

Position details

• Title: Sr. Data Engineer
• Department: Information Technology
• Reports to: Sr. Manager, Data Engineering
• Location: Dearborn, MI
• Job Classification: Remote
• FLSA Status: Exempt
• Job Band: Professional

Physical requirements and working conditions

• Normal office environment; extended periods of time sitting, standing, and typing on a computer
• Willingness to work some weekends if necessary
• Remote role with no regular requirement to be on-site; travel on-site limited to special events
• Carhartt is a tobacco-free workplace