Sr. Data Engineer
- Compensation
- Not disclosed
- Location
- Dearborn, MI, US
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Data engineering
- Posted
Skills
Must have
- 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, a
- Physical Requirements and Working Conditions
- Normal office environment. Extended periods of time sitting, standing, typing on a computer is required. Willing to work some weekends if necessary.
- This position has a Remote location: Associate will have no regular requirement to be on-site. Travel on-site is limited to special events. Carhartt is a tobacco free workplace.
- #LI-REMOTE
Full description
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
Job Summary
The primary responsibility of this position is to design, build, optimize, and support secure, reliable, and scalable enterprise data solutions. The Senior Data Engineer provides technical leadership for Azure Databricks and Lakehouse architecture, data pipeline design and orchestration, data modeling and performance optimization, cloud-native data platforms, data governance and quality, and AI/ML-ready data products. This role mentors engineers and collaborates across business, analytics, architecture, security, and application teams to deliver trusted data for reporting, advanced analytics, machine learning, and operational use.
Inspired by Hard Work
At Carhartt, the values of hard work—dependability, honesty, and trust—are rooted in the legacy of our founder, Hamilton Carhartt. His commitment to serving hardworking people continues to inspire everything we do. Guided by his legacy and our mission—We serve and protect all hardworking people by building durable products—we remain dedicated to upholding these principles in every decision we make and every product we create.
Associate 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-native services.
Design and evolve Lakehouse architecture using Delta Lake and Azure Data Lake Storage, including reusable data products and medallion-oriented data layers where appropriate.
Create and optimize conceptual, logical, dimensional, relational, and physical data models that are aligned with business meaning and analytical requirements.
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 data workloads.
Apply data governance and quality practices, including metadata, cataloging, validation, reconciliation, security, privacy, retention, and access controls.
Engineer trusted, well-documented, and reusable datasets and features that 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 architecture decisions and tradeoffs.