MDM Data Engineer
Gravity Hair Salon, LLC
Charlotte, NC, United States
about 1 month ago
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Role details
Contract type
Temporary to permanent
Employment type
Full-time (> 32 hours)
Compensation
$125,000.0 - $150,000.0
Working hours
Regular working hours
Job source
Tech stack
Customer Data Management
Data Architecture
Data Deduplication
Information Engineering
Extract Transform Load (ETL)
DevOps
Python (Programming Language)
Standard Sql
SQL Databases
Sql Optimization
Data Management
Data Pipelines
Job description
The resource will be embedded within the Client Pod and work closely with:
- 2 Data Engineers (including this hire)
- 1 Business Analyst
- 1 Product Manager
- Shared Services:
- DBA
- DevOps Engineer
- UI resources
Reports through the MDM Technology organization
Day-to-Day Responsibilities
- Build and maintain scalable data pipelines for a custom MDM platform.
- Work closely with product teams and shared services.
- Develop within a Python and SQL-based data environment.
- Collaborate with developers across multiple teams.
- Support data quality and pipeline reliability.
- Participate in technical discussions and architecture decisions (not expected to own strategy).
Requirements
- Strong Python development experience (major Python shop)
- Advanced SQL skills
- Experience designing and building scalable ETL/data pipelines
- Strong understanding of:
- Data architecture
- Data quality
- Pipeline design
- Ability to work collaboratively across technical teams
Nice-to-Haves
- Previous technical lead or team lead experience
- Experience in medium-to-large enterprise environments
- Client/customer/master data experience
- CRM-related data experience
- Experience with:
- Customer data
- Sales data
- Deduplication of people/client records
Desired Personality cultural fit is very important. Ideal candidates should:
- Be vocal and engaged
- Ask questions
- Be naturally curious
- Share opinions confidently
- Communicate well with technical teammates
- Not be passive or overly quiet
Candidate Evaluation Focus Managers wants candidates who can clearly demonstrate:
- Real-world pipeline development experience
- Ability to explain architecture decisions
- Depth of technical understanding
- Practical experience rather than buzzwords
- Strong communication skills
Key Takeaways
- Building scalable data pipelines is the single most important technical requirement.
- Python and SQL expertise are critical.
- Enterprise-scale data engineering experience is preferred.
- Client/master data experience is a strong differentiator.
- Communication and curiosity are major hiring factors.
- Suppliers should provide narrative-based video responses instead of checkbox technical screenings.
- Fast feedback cycle (48 hours) is a priority to keep candidates engaged.
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