The Leading Industrial Technology Partner for Car Wash Solutions
Senior Data Engineer
Location
Maine
Posted
2 days ago
Salary
$135K - $160K / year
Seniority
Senior
Job Description
Senior Data Engineer
National Carwash Solutions
• Design, build, and maintain data pipelines and lakehouse architecture • Develop and maintain SQL-based and PySpark transformations • Own data ingestion across enterprise sources • Partner with analysts and stakeholders to translate requirements • Develop Tableau data sources and enabling self-service analytics • Implement data quality practices and monitor pipelines • Establish standards for data modeling and pipeline architecture • Support AI workflows by providing curated data access • Manage platform configuration, cost, and performance • Troubleshoot data issues and resolve root causes
Job Requirements
- 5 or more years of professional data engineering experience
- Strong hands-on experience with Databricks
- Expert-level SQL skills
- Demonstrated experience in data ingestion from SaaS sources
- Working knowledge of major ERP, CRM, or HRIS data models
- Strong proficiency in Python
- Experience with cloud platforms (AWS preferred)
- Experience building data sources for BI tools
- Excellent written and verbal communication skills
- Bachelor’s degree in Computer Science or related field
Benefits
- medical, dental, and vision insurance
- a 401(k) plan with company match
- paid time off and company holidays
- life and disability insurance
- remote work flexibility
- professional development support
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AMS Data Platform Support Specialist
ReplyReply designs and implements innovative solutions in the areas: Digital Services, Technology and Consulting.
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• Забезпечувати коректність, узгодженість і доступність ключових бізнес-метрик для прийняття рішень на основі надійних даних. • Координувати роботу суміжних спеціалістів та формувати технічні вимоги до розвитку всієї data-інфраструктури компанії. • Перетворювати складні бізнес-вимоги та гіпотези у фінальні, структуровані data marts. • Постановка задач та контроль виконання робіт контрактними спеціалістами (Data Engineering / DevOps). • Впроваджувати практики контролю якості даних та управління ризиками для забезпечення їхньої цілісності. • Документувати основні бізнес-метрики (логіка розрахунку, джерела) та впроваджувати процеси пріоритезації задач.




