Sr. Data Engineer
Carhartt, Inc.24 days ago
Dearborn, MI, USASenior
Responsibilities
- Design, develop, test, deploy, and support scalable batch and streaming data pipelines using Azure Databricks, Azure Data Factory, Python, PySpark, SQL, and related cloud services.
- Design and evolve Lakehouse architecture using Delta Lake and Azure Data Lake Storage, including reusable data products and medallion-oriented data layers.
- Create and optimize conceptual, logical, dimensional, relational, and physical data models.
- Optimize pipelines, SQL queries, clusters, storage layouts, and processing patterns for performance, reliability, scalability, and cost effectiveness.
- Implement orchestration, dependency management, scheduling, monitoring, logging, alerting, error handling, recovery, lineage, and observability for production workloads.
- Apply data governance and quality practices covering metadata, cataloging, validation, reconciliation, security, privacy, retention, and access controls.
- Engineer trusted and reusable datasets and features for reporting, 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 architecture decisions.
- Mentor data engineers through pairing, technical guidance, code reviews, troubleshooting, coaching, and documentation.
- Partner with business stakeholders, analysts, data scientists, product owners, architects, security teams, application teams, and vendors.
- Apply Git-based source control, automated testing, CI/CD, deployment automation, and infrastructure configuration.
- Provide advanced production support, root-cause analysis, corrective actions, and continuous improvement for complex data platform incidents.
Requirements
- Bachelor’s degree in Computer Science, Information Systems, Engineering, Data Science, or a related technical field, or equivalent related experience.
- 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, including batch and streaming patterns, 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, Azure Data Factory, 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, metadata, cataloging, lineage, data quality, security, privacy, retention, and access-control principles.
- Experience preparing governed and documented data products for reporting, advanced analytics, data science, machine learning, generative AI, and 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 in architecture, solution design, engineering standards, design reviews, mentoring, code reviews, reusable patterns, and technical guidance.
- Excellent verbal and written communication and strong cross-functional collaboration skills.
- Ability to isolate complex problems, evaluate options, make practical decisions, and provide advanced production support during critical incidents.
- Graduate degree and professional cloud or data engineering certification are preferred.
Benefits
- Comprehensive medical, dental, and vision insurance for associates and dependents.
- Short-term and long-term disability insurance, life insurance, and an employee assistance program.
- 401(k) plan with employer matching contributions.
- Paid time off and designated paid holidays.
- Remote position with no regular on-site requirement; travel is limited to special events.
- Normal office environment with extended periods of sitting, standing, and computer typing; occasional weekend work may be required.